Expanded and clarified the README with detailed motivation, methodology, and evaluation of the Geometry Preserving Categorical Encoder (GPCE). Replaced the previous results image with five new figures (fig1.png to fig5.png) illustrating model accuracy comparisons across datasets and encoding methods.
Added datasets/bank.csv containing banking data and results/bank.png as an output image. Updated main.py to support the new dataset and generate results.
Added gpc_encoder.py implementing the Geometry Preserving Category Encoder (GPCE) for categorical feature encoding. Introduced main.py, a script for loading data, applying various encoders (GPCE, Label, OneHot, Target), training multiple classifiers, evaluating accuracy, and visualizing results. Also added a .gitignore for Python virtual environments and cache files.
seung6lee
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