igrigorik/decisiontree
ID3-based implementation of the ML Decision Tree algorithm
Implements both discrete and continuous ID3 tree learning with automatic threshold discovery for numeric features, generating binary partitions (e.g., temperature > 20°C). Includes rule extraction via C4.5-style pruning and ensemble bagging with majority voting, plus Graphviz visualization for tree analysis. Built as a Ruby library with fallback prediction when no branches match input data.
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Oct 31, 2018
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