commit 9ec39d97b775ac84b986420cf3528583e378fbe1 parent fa6e1bfdf462d007431326ece603e2c6d27c2d44 Author: AndrewLockVI <andrew@laack.co> Date: Fri, 9 May 2025 10:42:17 -0500 Updated readme with links and a better description of the repository. Diffstat:
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diff --git a/README.md b/README.md @@ -1,10 +1,25 @@ # CART-ELC -This is the source code for the implementation of CART-ELC we used in our paper. +This repository contains the following: -Also included in this repository are our implementations of HHCART(A) and HHCART(D). These are not described in our usage section, but they are simple oblique decision tree classifiers written in Python. +### Implementations -**Note:** The .tex source files for both the paper and an accompanying presentation will be added to this repository once the paper has been published. +| Model | Language | Notes | +|-------------|-----------------|--------------------------------------------------------| +| CART-ELC | C++ / Python | Includes C++ tests | +| HHCART(A) | Python | See [HHCART](https://doi.org/10.48550/arXiv.1504.03415)| +| HHCART(D) | Python | See [HHCART](https://doi.org/10.48550/arXiv.1504.03415)| + +### Results + +- Experiment scripts for HHCART(A), HHCART(D), and CART-ELC +- Experimental results for CART-ELC + +### Documentation + +- Usage instructions / implementation details +- Source files for our [paper under review at TMLR](https://doi.org/10.48550/arXiv.2505.05402) +- Source files for our presentation # Usage