Metadata-Version: 2.1
Name: model-selection
Version: 0.0.1
Summary: A Library which provides more information about suitable Machine learning algorithm for your dataset
Home-page: https://github.com/ManikandanJeyabal/ChooseMyALGO
Author: Manikandan Jeyabal
Author-email: ManikandanJeyabal029@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown

# Model Selection

### Scope of This Project
- As a beginner in Data science/Machine learning field, most of us having issue in **Feature Selection**,
**Feature Extraction** and **Model Selection**. Algorithm-Finder can help you to solve this problem. using Algorithm-Finder
you can achieve the below tasks and more.
    - **Model Selection**
    - **Feature Selection**
    - **Feature Extraction**
    - **Optimized tuning parameters**

- This package mainly used scikit-learn for most of the estimators, by using Algorithm-Finder you can apply your dataset
on below models
    - ALL --> ALL IN
    - MLR --> MultiLinearRegression
    - POLY --> PolynomialRegression
    - SVR --> SupportVectorRegression
    - DTREE --> DecisionTreeRegression & DecisionTreeClassification
    - RFR --> RandomForestRegression
    - SIGMOID --> LogisticRegression
    - KNN --> K-NearestNeighbours Classifier
    - SVM --> SupportVectorMachine Classifier
    - RFC --> RandomForestClassifier
    - BAYESIAN --> NaiveBayesClassifier

