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This package contains the Decition Tree algrotihm implementation.

Project description

Decision Tree algorithm from scratch

This repository contains Decision Tree implementation from scratch for classification problem.

About

This Decision Tree implementation is based on Leaf-wise algorithm.

  • Supports bins hyperparameter for speeding up the algorithm.
  • Supports Feature Importance calculation, which can help to understand the importance of features.
  • Supports classification heuristics:
    • Entropy and Information Gain,
    • Gini Impurity and Gini Gain,
  • Supports regression heuristics:
    • MSE and MSE Gain.

Dependencies

To install all required dependencies, execute the following command:

pip install requirements.txt

Usage

To start main script, execute the following command:

python main.py [OPTIONS]

Available options

  • -e, --example (required) - type of example to run. Available examples: classification.
  • -c, --config (required) - path to configuration file.

Tests

Test cases are placed in tests/ folder. To run tests use pytest module with the following command:

pytest tests/

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