Metadata-Version: 2.4
Name: milieudefensie
Version: 0.0.1
Summary: Machine learning tools for environmental analysis
Author-email: Data team <data@milieudefensie.nl>
Project-URL: Homepage, https://milieudefensie.nl
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy<3.0.0,>=2.0.0
Requires-Dist: pandas<3.0.0,>=2.0.0
Requires-Dist: scikit-learn<2.0.0,>=1.0.0
Requires-Dist: matplotlib>=3.0.0
Requires-Dist: plotly>=6.0.0
Requires-Dist: shap>=0.40.0
Requires-Dist: xgboost>=3.0.0
Requires-Dist: lightgbm>=4.0.0
Requires-Dist: catboost>=1.0.0
Requires-Dist: tqdm>=4.0.0
Requires-Dist: requests>=2.0.0
Dynamic: license-file

# Decision Tree Visualization and Classification Analysis Toolkit

![Python](https://img.shields.io/badge/python-3.8%2B-blue)
![License](https://img.shields.io/badge/license-MIT-green)

A comprehensive Python package for creating interactive decision tree visualizations and performing advanced classification model analysis.

## Features

- **Interactive HTML Decision Trees**: Visualize decision paths with D3.js
- **Automated Model Comparison**: Evaluate multiple classifiers with one function
- **Feature Importance Analysis**: Multiple methods including SHAP, permutation, and native importance
- **Probability Analysis**: Visualize prediction distributions
- **Data Preprocessing**: Automatic handling of categorical and numerical variables

## Installation

```bash
pip install -e .
