bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/526034ef035d076e7e0104ae --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/526034fc035d076e7f0235e0 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/52603504035d076e80011c4c --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/526034fc035d076e7f0235e0 --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/526034fc035d076e7f0235e0 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/526034fc035d076e7f0235e0 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/526035e1035d076e7d01905b --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/526035f1035d076e7f02361b --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/526035ff035d076e8101438e --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/5260360b035d076e80011c75 --model model/526035ff035d076e8101438e --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/52603662035d076e7d01906f --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/526036b0035d076e80011c98 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/526037bd035d076e7f0236c4 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/526037e6035d076e7d01909c --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5282c80ac38c592039000072 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5282c80fc38c59203900007c --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5282c812c38c592039000082 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5282c80fc38c59203900007c --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5282c80fc38c59203900007c --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5282c80fc38c59203900007c --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/5282c857c38c592039000144 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/5282c85ec38c592039000151 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/5282c866c38c59203900015a --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/5282c86ac38c592039000164 --model model/5282c866c38c59203900015a --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/5282c875c38c59203900017a --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282c87cc38c5920390001a6 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/5282c898c38c5920390001ec --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/5282c8d4c38c59203900029d --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/5282c8eec38c5920390002ce --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/5282c8eec38c5920390002ce --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/5282c8eec38c5920390002ce --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282c945c38c5920390003c5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/5282c954c38c5920390003e1 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5282c9b6035d074e9200c687 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5282c9c4035d074e9101c95b --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5282c9cc035d074e93014a23 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5282c9c4035d074e9101c95b --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5282c9c4035d074e9101c95b --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5282c9c4035d074e9101c95b --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/5282cab0035d074e93014a5a --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/5282cac1035d074e9101c9a8 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/5282cad0035d074e9400e976 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/5282cadb035d074e9200c6af --model model/5282cad0035d074e9400e976 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/5282cb02035d074e9101c9b7 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282cb3b035d074e9500b60a --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/5282cb88035d074e93014a7f --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/5282cc48035d074e9500b62e --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/5282cc8e035d074e93014abf --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/5282cc8e035d074e93014abf --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/5282cc8e035d074e93014abf --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282cdc4035d074e9400e9d7 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/5282cde7035d074e9400e9e6 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5282cf0b035d074e9200c740 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5282cf18035d074e9400ea13 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5282cf21035d074e9500b67d --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5282cf18035d074e9400ea13 --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5282cf18035d074e9400ea13 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5282cf18035d074e9400ea13 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/5282d001035d074e9400ea41 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/5282d011035d074e9200c760 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/5282d01e035d074e9200c763 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/5282d02e035d074e9101cad3 --model model/5282d01e035d074e9200c763 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/5282d04d035d074e93014b4b --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282d08a035d074e93014b58 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/5282d0e4035d074e9101cafa --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/5282d1b6035d074e93014b7e --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/5282d1fe035d074e9400ea83 --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/5282d1fe035d074e9400ea83 --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/5282d1fe035d074e9400ea83 --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282d337035d074e9500b6f5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/5282d36a035d074e9200c7ca --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5282d468035d074e93014c16 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5282d475035d074e9200c7ee --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5282d483035d074e93014c19 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5282d475035d074e9200c7ee --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5282d475035d074e9200c7ee --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5282d475035d074e9200c7ee --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/5282d58d035d074e9101cc14 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/5282d59e035d074e93014c4e --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/5282d5ae035d074e9101cc1b --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/5282d5bb035d074e9101cc21 --model model/5282d5ae035d074e9101cc1b --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/5282d5d8035d074e9101cc2b --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282d61b035d074e9500b738 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/5282d661035d074e9400eb34 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/5282d72c035d074e9200c846 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/5282d786035d074e9101cc9e --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/5282d786035d074e9101cc9e --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/5282d786035d074e9101cc9e --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5282d8b0035d074e9500b76c --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/5282d8d4035d074e93014cd8 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/528fa752035d07728100ace7 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/528fa762035d07728000c369 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/528fa771035d07728000c36c --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/528fa762035d07728000c369 --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/528fa762035d07728000c369 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/528fa762035d07728000c369 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/528fa864035d07728000c39c --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/528fa878035d07727f008a51 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/528fa887035d07728000c3a6 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/528fa894035d07727f008a55 --model model/528fa887035d07728000c3a6 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/528fa8b4035d07727d009ed0 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/528fa902035d07727e01018f --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/528fa972035d07727e0101b4 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/528faa49035d07727e0101f7 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/528faa9b035d07727d009f1a --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/528faa9b035d07727d009f1a --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/528faa9b035d07727d009f1a --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/528fabf7035d07727e010273 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/528fac22035d07727e01027f --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/528fb09f035d07727d009f76 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/528fb0ae035d07728000c46d --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/528fb0b9035d07728000c473 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/528fb0ae035d07728000c46d --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/528fb0ae035d07728000c46d --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/528fb0ae035d07728000c46d --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/528fb1ba035d07728100adab --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/528fb1cd035d07727f008b12 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/528fb1dc035d07727d009fa3 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/528fb1ea035d07728000c49a --model model/528fb1dc035d07727d009fa3 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/528fb213035d07728100adb4 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/528fb26e035d07728100adc7 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/528fb2bf035d07728100add6 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/528fb393035d07728100adee --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/528fb3e3035d07728100adf8 --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/528fb3e3035d07728100adf8 --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/528fb3e3035d07728100adf8 --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/528fb534035d07727e010391 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/528fb567035d07728100ae1e --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/528fb987035d07727e0103c7 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/528fb99d035d07728000c56e --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/528fb9a8035d07728000c571 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/528fb99d035d07728000c56e --test ../data/test_iris.csv --number-of-models 10 --no-replacement --tag my_ensemble --store --output ./scenario5/predictions.csv
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/528fb99d035d07728000c56e --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/528fb99d035d07728000c56e --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/528fbaaf035d07727f008bac --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/528fbac3035d07728100ae67 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/528fbad2035d07727d00a043 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/528fbade035d07727e010410 --model model/528fbad2035d07727d00a043 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/528fbb02035d07728000c59f --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/528fbb46035d07728000c5af --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/528fbb8f035d07727e010436 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/528fbc79035d07727d00a077 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/528fbcce035d07728000c5ff --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/528fbcce035d07728000c5ff --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/528fbcce035d07728000c5ff --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/528fbe3e035d07728100aecf --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/528fbe68035d07727f008c07 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5292a645035d07728100b674 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5292a651035d07728100b678 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5292a659035d07728100b67b --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5292a651035d07728100b678 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5292a651035d07728100b678 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5292a651035d07728100b678 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/5292a744035d07727e0116fa --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/5292a74d035d07727f0091d8 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/5292a74d035d07727f0091d8 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5292a8e9035d07727f0091e8 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5292a8f5035d07728100b693 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5292a8ff035d07728000d45d --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5292a8f5035d07728100b693 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5292a8f5035d07728100b693 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5292a8f5035d07728100b693 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/5292a9e3035d07728100b6ae --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/5292a9ec035d07728000d47d --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/5292a9ec035d07728000d47d --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5292aab7035d07727d00a617 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5292aac3035d07727e011766 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5292aacc035d07727e011769 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5292aac3035d07727e011766 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5292aac3035d07727e011766 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5292aac3035d07727e011766 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/5292abb8035d07727e0117b4 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/5292abc1035d07727e0117b7 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/5292abc1035d07727e0117b7 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/5293d947035d07728000d93c --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/5293d955035d07727e011e00 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/5293d95e035d07728100ba0e --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/5293d955035d07727e011e00 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/5293d955035d07727e011e00 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/5293d955035d07727e011e00 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/5293da03035d07727e011e25 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/5293da0c035d07727d00a8b8 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/5293da0c035d07727d00a8b8 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/5293da64035d07727e011e4f --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/5293da74035d07727e011e56 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/5293da81035d07727e011e59 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/5293da8c035d07728100ba45 --model model/5293da81035d07727e011e59 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/5293daab035d07727e011e69 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5293daea035d07727d00a8dd --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/5293db28035d07727f009491 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/5293dbfc035d07727e011ef5 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/5293dc43035d07728000d9a5 --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/5293dc43035d07728000d9a5 --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/5293dc43035d07728000d9a5 --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/5293dd69035d07727e011f7d --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/5293dd8f035d07727e011f8f --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/529e2436035d07727e037cd4 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/529e2446035d07728002c3b8 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/529e2452035d07727f01f5ad --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/529e2446035d07728002c3b8 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/529e2446035d07728002c3b8 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/529e2446035d07728002c3b8 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/529e2526035d0772810265e2 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/529e2531035d07727f01f5cd --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/529e2531035d07727f01f5cd --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/529e2599035d07728002c3e9 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/529e25ac035d07727f01f5e5 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/529e25ba035d07727e037d11 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/529e25c6035d0772810265f8 --model model/529e25ba035d07727e037d11 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/529e25e3035d077281026601 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv
bigmler --source source/529e25ef035d07727d02200c --max-categories 1 --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv
bigmler --dataset dataset/529e25f3035d07727e037d49 --max-categories 1 --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/52ab353c035d0779e2011106 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/52ab3554035d0779df0139d4 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/52ab355d035d0779e001aaf7 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/52ab3554035d0779df0139d4 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/52ab3554035d0779df0139d4 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/52ab3554035d0779df0139d4 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/52ab360c035d0779e001ab31 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/52ab3617035d0779e001ab34 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/52ab3617035d0779e001ab34 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52ab368b035d0779df0139eb --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52ab369f035d0779dd01619f --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52ab36af035d0779dd0161a2 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52ab36bd035d0779dc0124ba --model model/52ab36af035d0779dd0161a2 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52ab36db035d0779dc0124be --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv
bigmler --source source/52ab36e7035d0779dd0161b4 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv
bigmler --dataset dataset/52ab36eb035d0779dc0124c1 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1
bigmler --source source/52b2420d035d073bb800347a --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv
bigmler --dataset dataset/52b2421a035d073bb900543c --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv
bigmler --model model/52b24223035d073bba0027c6 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1
bigmler --dataset dataset/52b2421a035d073bb900543c --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted"
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted"
bigmler --dataset dataset/52b2421a035d073bb900543c --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv
bigmler --dataset dataset/52b2421a035d073bb900543c --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full
bigmler --dataset dataset/52b242c6035d073bba0027d7 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv
bigmler --ensemble ensemble/52b242cf035d073bba0027da --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10
bigmler --ensemble ensemble/52b242cf035d073bba0027da --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52b24331035d073bb80034a1 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52b24341035d073bb6004123 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52b2434e035d073bb900548a --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52b24358035d073bb9005493 --model model/52b2434e035d073bb900548a --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52b24372035d073bb900549d --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/52b243b1035d073bb80034ae --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv
bigmler --multi-label --dataset dataset/52b243f6035d073bb90054ba --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52b244e1035d073bb7002e59 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52b24523035d073bb6004185 --evaluate --store --output ./scenario_ml_e3/evaluation
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52b24523035d073bb6004185 --evaluate --store --output ./scenario_ml_e4/evaluation
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52b24523035d073bb6004185 --evaluate --store --output ./scenario_ml_e5/evaluation
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1
bigmler --multi-label --source source/52b2463f035d073bb9005575 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv
bigmler --multi-label --dataset dataset/52b24665035d073bb900557c --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52c59a9c035d0719ce00075e --test-source source/52c59aa6035d0719cd0005b6 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52c59acc035d0719cb000343 --test-dataset dataset/52c59ad1035d0719ce000767 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52c59b55035d0719cb00034b --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52c59b69035d0719ce000774 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52c59b89035d0719cb000351 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52c59b69035d0719ce000774 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52c59b69035d0719ce000774 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52c59b69035d0719ce000774 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52c59c7d035d0719cb00036e --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52c59c8b035d0719cd0005d7 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52c59c8b035d0719cd0005d7 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52c59d99035d0719cd0005e6 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52c59db6035d0719ce0007ac --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52c59ddf035d0719cf000413 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52c59df8035d0719cf000416 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52c59e06035d0719ce0007b1 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52c59e13035d0719cc0003d8 --model model/52c59e06035d0719ce0007b1 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52c59e30035d0719cb00038d --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52c59eb4035d0719cd000605 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52c59f10035d0719cd000608 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52c59fce035d0719ce0007da --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52c5a03e035d0719cd000618 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52c5a1a0035d0719cd00063c --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52c5a220035d0719ce000802 --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52c5a220035d0719ce000802 --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52c5a220035d0719ce000802 --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52c5a44e035d0719cc00045f --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52c5a490035d0719ce00084c --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52cc96fb035d074b0d000090 --test-source source/52cc9702035d074b0e00007c --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52cc9711035d074b100000c6 --test-dataset dataset/52cc9715035d074b100000cc --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52cc975e035d074b100000db --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52cc976a035d074b0f0000b1 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52cc9770035d074b0d0000a2 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52cc976a035d074b0f0000b1 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52cc976a035d074b0f0000b1 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52cc976a035d074b0f0000b1 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52cc97f8035d074b0d0000c3 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52cc9800035d074b0d0000c6 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52cc9800035d074b0d0000c6 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52cc9863035d074b0d0000e2 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52cc986d035d074b100000ff --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52cc9888035d074b0c00013a --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52cc989e035d074b0d0000e7 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52cc98a8035d074b0c000146 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52cc98b2035d074b0c000149 --model model/52cc98a8035d074b0c000146 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52cc98d3035d074b1000010a --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52cc9913035d074b0f0000d8 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52cc992d035d074b0c00016a --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52cc9997035d074b0f0000ea --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52cc99d3035d074b0f0000f2 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52cc9a87035d074b0f000100 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52cc9ac5035d074b10000156 --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52cc9ac5035d074b10000156 --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52cc9ac5035d074b10000156 --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52cc9be6035d074b0e0000db --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52cc9c04035d074b0c00024a --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d04c2b035d07719b000006 --test-source source/52d04c4f035d07719c000009 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d04cad035d07719c00000c --test-dataset dataset/52d04cbd035d077199000003 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d04dd2035d07719d00000f --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d04dda035d07719900000c --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d04ddf035d07719900000f --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d04dda035d07719900000c --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d04dda035d07719900000c --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d04dda035d07719900000c --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d05053035d07719d00002a --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d05062035d07719b00001b --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d05062035d07719b00001b --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d053f2035d07719900002d --test-source source/52d053fc035d07719d00003b --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d0541e035d07719d00003e --test-dataset dataset/52d05423035d07719b00002c --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d055fa035d07719a00003c --test-source source/52d05608035d07719a000042 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d056d6035d07719900004e --test-dataset dataset/52d056db035d077199000051 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d06945035d07719b000045 --test-source source/52d06952035d07719b00004b --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d06948035d07719c000050 --test-dataset dataset/52d06956035d07719900005d --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d2b881035d0709aa000096 --test-source source/52d2b891035d0709a800005e --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d2b8a5035d0709a8000061 --test-dataset dataset/52d2b8ab035d0709aa0000a2 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d2b907035d0709a800006b --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d2b91a035d0709aa0000ae --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d2b924035d0709a7000061 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d2b91a035d0709aa0000ae --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d2b91a035d0709aa0000ae --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d2b91a035d0709aa0000ae --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d2b9eb035d0709aa0000cb --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d2b9fe035d0709a8000080 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d2b9fe035d0709a8000080 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d2ba9e035d0709aa0000db --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d2bab3035d0709a7000089 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d2badf035d0709ab000098 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d2baf9035d0709ab00009b --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d2bb0a035d0709a9000166 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d2bb16035d0709a900016c --model model/52d2bb0a035d0709a9000166 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d2bb38035d0709a9000178 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52d2bb9a035d0709aa0000f7 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d2bbc5035d0709a80000ab --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d2bc64035d0709a70000b0 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d2bd2d035d0709a90001b0 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52d2bfe4035d0709a90001d6 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52d2c06a035d0709a80000d0 --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52d2c06a035d0709a80000d0 --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52d2c06a035d0709a80000d0 --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d2c20f035d0709a7000103 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d2c245035d0709aa000163 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --multi-label-fields type,class --label-separator : --training-separator , --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_1/predictions.csv --objective class --tag my_multilabelm_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d2c344035d0709aa00017d --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d2c387035d0709a7000129 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_mlm_1/models --test ../data/test_multilabel.csv --store --output ./scenario_mlm_4/predictions.csv --objective class --verbosity 0
bigmler --multi-label --model-tag my_multilabelm_1 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_mlm_5/predictions.csv --objective class --max-batch-models 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d5c73d035d073c0700025e --test-source source/52d5c74f035d073c0c0003cc --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d5c767035d073c0600016d --test-dataset dataset/52d5c76f035d073c07000264 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d5c7c6035d073c0c0003e7 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d5c7d0035d073c0a0001a8 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d5c7d7035d073c0c0003ea --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d5c7d0035d073c0a0001a8 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d5c7d0035d073c0a0001a8 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d5c7d0035d073c0a0001a8 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d5c86e035d073c07000287 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d5c876035d073c0c000414 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d5c876035d073c0c000414 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d5c8e1035d073c07000296 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d5c8eb035d073c0c00043b --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d5c902035d073c09000231 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d5c911035d073c0c000448 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d5c926035d073c070002a2 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d5c930035d073c0a0001d1 --model model/52d5c926035d073c070002a2 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d5c94c035d073c0c000451 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52d5c988035d073c0c000466 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d5c9a2035d073c070002b9 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d5ca01035d073c060001a1 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d5caa6035d073c070002e5 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52d5cc17035d073c0a0001f9 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52d5cc56035d073c0c0004c1 --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52d5cc56035d073c0c0004c1 --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52d5cc56035d073c0c0004c1 --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d5cd4e035d073c07000377 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d5cd6c035d073c0c000517 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --multi-label-fields type,class --label-separator : --training-separator , --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_1/predictions.csv --objective class --tag my_multilabelm_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d5ce21035d073c090002c9 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d5ce41035d073c070003a8 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_mlm_1/models --test ../data/test_multilabel.csv --store --output ./scenario_mlm_4/predictions.csv --objective class --verbosity 0
bigmler --multi-label --model-tag my_multilabelm_1 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_mlm_5/predictions.csv --objective class --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --label-separator : --training-separator , --multi-label-fields type,class --objective class --store --output-dir ./scenario_mlm_6 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi2.csv --label-separator : --training-separator , --multi-label-fields Colors,Movies,Hobbies --objective Hobbies --store --output-dir ./scenario_mlm_7 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --label-separator : --training-separator , --multi-label-fields type,class --objective class --store --output-dir ./scenario_mlm_6 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi2.csv --label-separator : --training-separator , --multi-label-fields Colors,Movies,Hobbies --objective Hobbies --store --output-dir ./scenario_mlm_7 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d81110035d073c0a0004ff --test-source source/52d81118035d073c0c000c26 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d81126035d073c0c000c2f --test-dataset dataset/52d8112a035d073c070007f2 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d8116e035d073c07000800 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d81179035d073c07000803 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d81180035d073c0c000c40 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d81179035d073c07000803 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d81179035d073c07000803 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d81179035d073c07000803 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d81218035d073c0a000527 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d81220035d073c0c000c61 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d81220035d073c0c000c61 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d8129c035d073c07000822 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d812a7035d073c0c000c83 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d812c5035d073c0900060f --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d812d4035d073c0c000c8b --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d812df035d073c0c000c94 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d812e9035d073c07000833 --model model/52d812df035d073c0c000c94 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d81318035d073c0700083c --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52d8135c035d073c0a000552 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d8137e035d073c0a000555 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d813f1035d073c0c000ccc --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d8148e035d073c0a000565 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52d81612035d073c060004fb --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52d8164d035d073c0c000d20 --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52d8164d035d073c0c000d20 --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52d8164d035d073c0c000d20 --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d8175d035d073c0c000d77 --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d8177c035d073c070008b2 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --multi-label-fields type,class --label-separator : --training-separator , --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_1/predictions.csv --objective class --tag my_multilabelm_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d81813035d073c0a0005c4 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d81832035d073c0a0005cd --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_mlm_1/models --test ../data/test_multilabel.csv --store --output ./scenario_mlm_4/predictions.csv --objective class --verbosity 0
bigmler --multi-label --model-tag my_multilabelm_1 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_mlm_5/predictions.csv --objective class --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --label-separator : --training-separator , --multi-label-fields type,class --objective class --store --output-dir ./scenario_mlm_6 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi2.csv --label-separator : --training-separator , --multi-label-fields Colors,Movies,Hobbies --objective Hobbies --store --output-dir ./scenario_mlm_7 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d9c892035d0767eb00000f --test-source source/52d9c89c035d0767e900000c --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d9c919035d0767e9000015 --test-source source/52d9c923035d0767ea000009 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9c939035d0767eb000018 --test-dataset dataset/52d9c945035d0767ed000018 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d9c9f6035d0767ea000018 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9ca24035d0767e9000028 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d9ca2d035d0767ea00001e --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d9ca24035d0767e9000028 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d9ca24035d0767e9000028 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9ca24035d0767e9000028 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d9cb11035d0767e9000055 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d9cb1d035d0767e9000058 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d9cb1d035d0767e9000058 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d9cbdd035d0767ec00003b --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d9cbf3035d0767e9000076 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d9cc45035d0767ed000052 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d9cc5c035d0767ed000058 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d9cc6d035d0767e900007e --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d9cc80035d0767ed000061 --model model/52d9cc6d035d0767e900007e --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d9ccaf035d0767e900008a --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52d9cd3f035d0767e90000a0 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9cd65035d0767e90000a6 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d9ce23035d0767ec000067 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d9ce27035d0767ec00006a --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d9d9f4035d0767ed00009c --test-source source/52d9d9fd035d0767e90000f0 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9da12035d0767ec0000a6 --test-dataset dataset/52d9da17035d0767e90000f6 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d9da8e035d0767eb000070 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9da9a035d0767ed0000ab --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d9daa1035d0767ea00006e --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d9da9a035d0767ed0000ab --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d9da9a035d0767ed0000ab --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9da9a035d0767ed0000ab --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d9db4e035d0767ea00007a --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d9db5b035d0767ec0000d0 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d9db5b035d0767ec0000d0 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d9dc1d035d0767e900014f --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d9dc2a035d0767e9000152 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d9dc64035d0767ec0000fa --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d9dc8f035d0767ea000090 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d9dc9b035d0767ed0000dc --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d9dca6035d0767eb000099 --model model/52d9dc9b035d0767ed0000dc --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d9dcc5035d0767ec000109 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52d9dd2c035d0767ed0000f3 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9dd4a035d0767ec00011b --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52d9de41035d0767e9000195 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52d9def6035d0767ed00012b --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d9e15a035d0767e90001d4 --test-source source/52d9e164035d0767e90001dd --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9e174035d0767e90001e0 --test-dataset dataset/52d9e178035d0767ec000165 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d9e724035d0767e9000207 --test-source source/52d9e72d035d0767ec000185 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9e743035d0767e9000210 --test-dataset dataset/52d9e74b035d0767e9000216 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d9e7bb035d0767e9000221 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9e7cc035d0767ec000195 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d9e7d4035d0767e9000227 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d9e7cc035d0767ec000195 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d9e7cc035d0767ec000195 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9e7cc035d0767ec000195 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d9e88d035d0767e900024a --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d9e89f035d0767eb000130 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d9e89f035d0767eb000130 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d9e94e035d0767e9000262 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d9e95c035d0767ea00011c --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d9e99b035d0767eb000146 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d9e9b0035d0767e900026c --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d9e9bf035d0767ec0001be --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d9e9ca035d0767ea000122 --model model/52d9e9bf035d0767ec0001be --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d9e9e2035d0767ed0001a5 --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52d9ea58035d0767ed0001ac --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9ea76035d0767e9000290 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52d9edd7035d0767ea000143 --test-source source/52d9eddf035d0767e90002a7 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9edff035d0767e90002aa --test-dataset dataset/52d9ee04035d0767eb000174 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52d9ee71035d0767ec000203 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9ee82035d0767ea000160 --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52d9ee8a035d0767ec000206 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52d9ee82035d0767ea000160 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52d9ee82035d0767ea000160 --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52d9ee82035d0767ea000160 --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52d9ef33035d0767ed0001d6 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52d9ef3b035d0767e90002e9 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52d9ef3b035d0767e90002e9 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52d9f006035d0767eb000192 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52d9f014035d0767eb000198 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52d9f05b035d0767eb00019d --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52d9f06c035d0767eb0001a3 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52d9f077035d0767ed0001ec --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52d9f081035d0767e900031a --model model/52d9f077035d0767ed0001ec --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52d9f09f035d0767eb0001ac --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52da926c035d0767eb000324 --test-source source/52da9275035d0767e900054e --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52da928d035d0767eb00032d --test-dataset dataset/52da9292035d0767e9000551 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52da92ed035d0767ed00039f --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52da92fa035d0767eb00033c --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52da9308035d0767ea0002ed --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52da92fa035d0767eb00033c --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52da92fa035d0767eb00033c --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52da92fa035d0767eb00033c --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52da93d2035d0767e900057a --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52da93e5035d0767ea000304 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52da93e5035d0767ea000304 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52da9476035d0767ed0003c3 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52da9492035d0767e9000593 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52da94b6035d0767ea000319 --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52da94ce035d0767ec00045e --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52da94e1035d0767ec000464 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52da94ee035d0767e900059b --model model/52da94e1035d0767ec000464 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52da9515035d0767eb00036f --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52da956e035d0767e90005b7 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52da9595035d0767e90005bd --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52da960f035d0767ea000339 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52da96c3035d0767eb00039d --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52da9847035d0767e90005ea --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52da9898035d0767e90005fc --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52da9898035d0767e90005fc --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52da9898035d0767e90005fc --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52da99fd035d0767ec0004ef --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52da9a2c035d0767ea000390 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --multi-label-fields type,class --label-separator : --training-separator , --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_1/predictions.csv --objective class --tag my_multilabelm_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52da9b1d035d0767e9000670 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52da9b4b035d0767e9000679 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_mlm_1/models --test ../data/test_multilabel.csv --store --output ./scenario_mlm_4/predictions.csv --objective class --verbosity 0
bigmler --multi-label --model-tag my_multilabelm_1 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_mlm_5/predictions.csv --objective class --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --label-separator : --training-separator , --multi-label-fields type,class --objective class --store --output-dir ./scenario_mlm_6 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi2.csv --label-separator : --training-separator , --multi-label-fields Colors,Movies,Hobbies --objective Hobbies --store --output-dir ./scenario_mlm_7 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --fields-map ../data/grades_fields_map.csv --store --output ./scenario_r1_r/predictions.csv --remote --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario_r1/predictions.csv --remote --verbosity 0
bigmler --source source/52de15ac035d071a6f000127 --test-source source/52de15b5035d071a68000219 --store --remote --output ./scenario_r2/predictions.csv --verbosity 0
bigmler --dataset dataset/52de15c3035d071a69000090 --test-dataset dataset/52de15c8035d071a69000093 --store --remote --output ./scenario_r3/predictions.csv --verbosity 0
bigmler --train ../data/grades.csv --test ../data/test_grades.csv --store --output ./scenario1_r/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario1/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --source source/52de160c035d071a670000c7 --test ../data/test_iris.csv --store --output ./scenario2/predictions.csv --verbosity 0
bigmler --dataset dataset/52de1617035d071a6f00013f --test ../data/test_iris.csv --store --output ./scenario3/predictions.csv --verbosity 0
bigmler --model model/52de161e035d071a610000a8 --test ../data/test_iris.csv --store --output ./scenario4/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --dataset dataset/52de1617035d071a6f00013f --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario5/predictions.csv --no-replacement --verbosity 0
bigmler --models ./scenario5/models --test ../data/test_iris.csv --store --output ./scenario6/predictions.csv --verbosity 0
bigmler --datasets ./scenario1/dataset --test ../data/test_iris.csv --store --output ./scenario7/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario8/predictions.csv --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1,./scenario5 --store --output ./scenario9/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_c.csv --method "confidence weighted" --verbosity 0
bigmler --combine-votes ./scenario1_r,./scenario1_r --store --output ./scenario10/predictions_p.csv --method "probability weighted" --verbosity 0
bigmler --dataset dataset/52de1617035d071a6f00013f --objective 0 --model-fields "petal length,petal width" --test ../data/test_iris.csv --store --output ./scenario11/predictions.csv --verbosity 0
bigmler --dataset dataset/52de1617035d071a6f00013f --cross-validation-rate 0.05 --store --output ./scenario12/cross-validation --verbosity 0
bigmler --train ../data/iris.csv --locale es_ES.UTF-8 --store --output ./scenario13/store_file --no-dataset --no-model --store
bigmler --train ../data/iris.csv --test ../data/test_iris.tsv --test-separator \t --store --output ./scenario14/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --test ../data/test_iris.csv --store --output ./scenario15/predictions.csv --max-batch-models 1 --prediction-header --prediction-fields "petal length,petal width" --prediction-info full --verbosity 0
bigmler --dataset dataset/52de16b8035d071a6f000162 --test ../data/test_iris.csv --number-of-models 10 --tag my_ensemble --store --output ./scenario16/predictions.csv --verbosity 0
bigmler --ensemble ensemble/52de16c9035d071a610000c3 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions2.csv --method threshold --threshold 10 --verbosity 0
bigmler --ensemble ensemble/52de16c9035d071a610000c3 --test ../data/test_iris.csv --tag my_ensemble --store --output ./scenario16/predictions3.csv --method threshold --threshold 1 --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_1 --verbosity 0
bigmler --dataset dataset/52de1755035d071a610000d2 --no-model --store --output-dir ./scenario_d_1 --new-fields ../data/new_fields.json --verbosity 0
bigmler --train ../data/iris.csv --no-model --store --output-dir ./scenario_d_2 --verbosity 0
bigmler --dataset dataset/52de1760035d071a690000b4 --no-model --store --output-dir ./scenario_d_2 --dataset-attributes ../data/attributes.json --verbosity 0
bigmler --evaluate --train ../data/iris.csv --store --output ./scenario_e1/evaluation
bigmler --evaluate --source source/52de1784035d071a6f00017f --output ./scenario_e2/evaluation
bigmler --evaluate --dataset dataset/52de17b1035d071a68000267 --output ./scenario_e3/evaluation
bigmler --evaluate --test ../data/iris.csv --model model/52de17be035d071a670000e5 --output ./scenario_e4/evaluation
bigmler --evaluate --dataset dataset/52de17c9035d071a68000270 --model model/52de17be035d071a670000e5 --output ./scenario_e5/evaluation
bigmler --evaluate --train ../data/iris.csv --test-split 0.2 --output ./scenario_e6/evaluation
bigmler --evaluate --test ../data/iris_permuted.csv --model model/52de17df035d071a690000bc --output ./scenario_e7/evaluation --fields-map ../data/fields_map.csv
bigmler --train ../data/iris.csv --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_1/predictions.csv --verbosity 0
bigmler --source source/52de181d035d071a68000298 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_2/predictions.csv --verbosity 0
bigmler --dataset dataset/52de183d035d071a690000c2 --max-categories 1 --objective species --test ../data/test_iris.csv --store --output ./scenario_mc_3/predictions.csv --verbosity 0
bigmler --models scenario_mc_1/models --method combined --test ../data/test_iris.csv --store --output ./scenario_mc_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --number-of-models 3 --store --output ./scenario_mle_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52de18a7035d071a690000cf --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52de194a035d071a610000f2 --number-of-models 3 --test ../data/test_multilabel.csv --store --output ./scenario_mle_3/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --evaluate --store --output ./scenario_ml_e1/evaluation --tag my_multilabel_e_1 --max-batch-models 1
bigmler --multi-label --source source/52de1aab035d071a61000104 --evaluate --store --output ./scenario_ml_e2/evaluation
bigmler --multi-label --dataset dataset/52de1ae9035d071a6800031d --evaluate --store --output ./scenario_ml_e3/evaluation --verbosity 0
bigmler --multi-label --models ./scenario_ml_e1/models --dataset dataset/52de1ae9035d071a6800031d --evaluate --store --output ./scenario_ml_e4/evaluation --verbosity 0
bigmler --multi-label --model-tag my_multilabel_e_1 --dataset dataset/52de1ae9035d071a6800031d --evaluate --store --output ./scenario_ml_e5/evaluation --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_1/predictions.csv --tag my_multilabel_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52de1c2a035d071a6f0001fe --test ../data/test_multilabel.csv --store --output ./scenario_ml_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52de1c59035d071a69000109 --test ../data/test_multilabel.csv --store --output ./scenario_ml_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_ml_1/models --test ../data/test_multilabel.csv --store --output ./scenario_ml_4/predictions.csv --verbosity 0
bigmler --multi-label --train ../data/multilabel.csv --label-separator : --training-separator , --test ../data/test_multilabel.csv --store --output ./scenario_ml_6/predictions.csv --tag my_multilabel_5 --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --test ../data/test_multilabel.csv --store --output ./scenario_ml_5/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --model-tag my_multilabel_5 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_ml_7/predictions.csv --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --multi-label-fields type,class --label-separator : --training-separator , --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_1/predictions.csv --objective class --tag my_multilabelm_1 --max-batch-models 1 --verbosity 0
bigmler --multi-label --source source/52de1cff035d071a6100014c --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_2/predictions.csv --verbosity 0
bigmler --multi-label --dataset dataset/52de1d21035d071a69000121 --objective class --model-fields " -type,-type - W,-type - A,-type - C,-type - S,-type - R,-type - T,-type - P" --test ../data/test_multilabel.csv --store --output ./scenario_mlm_3/predictions.csv --verbosity 0
bigmler --multi-label --models ./scenario_mlm_1/models --test ../data/test_multilabel.csv --store --output ./scenario_mlm_4/predictions.csv --objective class --verbosity 0
bigmler --multi-label --model-tag my_multilabelm_1 --labels Adult,Student --test ../data/test_multilabel.csv --store --output ./scenario_mlm_5/predictions.csv --objective class --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi.csv --label-separator : --training-separator , --multi-label-fields type,class --objective class --store --output-dir ./scenario_mlm_6 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --multi-label --train ../data/multilabel_multi2.csv --label-separator : --training-separator , --multi-label-fields Colors,Movies,Hobbies --objective Hobbies --store --output-dir ./scenario_mlm_7 --no-dataset --no-model --max-batch-models 1 --verbosity 0
bigmler --train ../data/iris.csv --balance --store --output-dir ./scenario_w_1 --verbosity 0
bigmler --train ../data/iris_w.csv --weight-field weight --store --output-dir ./scenario_w_2 --verbosity 0
