Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
-
Updated
Nov 6, 2024 - Jupyter Notebook
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Three MIP models for optimal classification tree: OCT, binOCT, flowOCT
Rolling Lookahead Decision Trees
Add a description, image, and links to the optimal-classification-tree topic page so that developers can more easily learn about it.
To associate your repository with the optimal-classification-tree topic, visit your repo's landing page and select "manage topics."