Custom implementation of Naïve Bayes and Decision Tree classifiers from scratch, applied to categorical datasets (Mushroom & Congressional Voting). No scikit-learn used—focus on core ML principles like entropy, Laplace smoothing, and tree traversal.
python machine-learning entropy naive-bayes classification decision-trees from-scratch information-gain mushroom-dataset voting-records
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Updated
May 8, 2025 - Python