Repository for the paper A benchmark of categorical encoders for binary classification, accepted at NeurIPS 2023, Datasets and Benchmarks track.

1. Install Python 3.8.10;
2. create and activate a virtual environment, we call it venv;
3. install dependencies with pip install -r requirements.

Our implementations of GLMM-based encoders require the rpy2 module and R to be installed. The R version we used is 4.2.2, with the lme4 package version 1.1-31.
To aggregate results with Kemeny aggregation, install and configure Gurobi and its Python API.

In the experiments directory.

All of the code necessary to reproduce the analysis and the plots is available in the analysis directory.