Metadata-Version: 2.1
Name: autooptimizer
Version: 0.7.8
Summary: AutoOptimizer is a python package for optimize ML algorithms.
Home-page: https://github.com/mrb987/autooptimizer
Author: MohammadReza Barghi
Author-email: info@genesiscube.ir
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
Requires-Dist: sklearn
Requires-Dist: numpy
Requires-Dist: matplotlib

AutoOptimizer provides tools to automatically optimize machine learning model for a dataset with very little user intervention.

It refers to techniques that allow semi-sophisticated machine learning practitioners and non-experts 
to discover a good predictive model pipeline for their machine learning algorithm task quickly,
with very little intervention other than providing a dataset.


#Prerequisites:

jupyterlab or: {sklearn, matplotlib, numpy}	


#Usage:


>Optimize scikit learn supervised, unsupervised and ensemble learning models using python.


{DBSCAN, KMeans, MeanShift,  LogisticRegression, LinearRegression, KNeighborsClassifier, KNeighborsRegressor,
RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier, SupportVectorClassifier, DecisionTree}


>Metrics for Your Regression Model


>Clear data by removing outliers

>>for more information visit: http://genesiscube.ir/index-6.html



#Contact and Contributing:
Please share your good ideas with us.
Simply letting us know how we can improve the programm to serve you better.
Thanks for contributing with the program.

>>https://github.com/mrb987/autooptimizer
>>info@Genesiscube.ir

