Machine learning classifiers project focused on building models from scratch/with libraries and evaluating performance using standard metrics (accuracy/precision/recall), proper data splitting, and clean experiment structure. Emphasis on correctness, numerical stability.
ml naive-bayes-classifier e2e decision-tree-classifier optimisation early-stopping gain-ratio stratified-cross-validation
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Updated
Jul 14, 2026 - Python