ml-helper 0.0.23

Helpers to speed up and structure machine learning projects

ML Helper

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Helpers to speed up and structure machine learning projects.

The library is available in Pypi

Installing

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The easiest way to install ml-helper is through pip

pip install ml-helper

To use it in your project, you must first import the library

from ml_helper.helper import Helper

And then create a Helper object with a dictionary of keys related to your project

KEYS = {
    'SEED': 1,
    'TARGET': 'y',
    'METRIC': 'r2',
    'TIMESERIES': True,
    'SPLITS': 5
}

hp = Helper(KEYS)

After this, you may use the helper object's many functions

Dependencies

ML-Helper requires:

• Python (>3.5)
• Numpy (>=1.16)
• Pandas (>=0.23.4)
• Seaborn (>=0.9)
• Scikit-learn (>=0.20)
• Natplotlib (>=3)
• Scipy (>=1)
• Imblearn
• Vecstack

Functionality

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The functionality is separated into 4 groups:

• Data Exploration
  • Missing Data
  • Boxplot of numerical variables
  • Coefficient of variation
  • Correlation (numerical and categorical)
  • Under Represented Features
  • Target Variable Distribution
  • Feature Importance
  • PCA Component Variance
• Data Preparation
  • Convert features to categories
  • Drop multiple columns
• Modeling
  • Cross Validation (with stratified kfolds, or time series split depending on use case)
    • Randomized Grid Search
  • Pipeline: Collection of models and pipeline steps that get performed and scored
  • Predict: Predict on unseen data
  • Stack Predict: Build a stacked model and perform a prediction
• Regression
  • Plots for predictions
• Classification
  • ROC Curve
  • Classification Report
• Others
  • Select features based on types
  • Split X and y
  • Plot models/pipelines

Working Examples

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If you wish to see the library in use, you may view the notebooks in the examples section.

Also, you can see the implementation in their corresponding Kaggle Kernels:

• Bike Sharing in Washington D.C.: Time Series Regression

• Employee Attrition: Classification

ML-Helper Coding Style

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Ml-Helper complies to PEP8 and uses black for coding standards

Versioning

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SemVer is used for versioning.

License

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This project is licensed under the MIT License - see the License file for details