Path-based adaptive weighting of random forest trees via decision path patterns delivers statistically significant accuracy gains on 36 binary classification benchmarks with minimal class-recall regression.
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Decision-Path Patterns as Tree Reliability Signals: Path-based Adaptive Weighting for Random Forest Classification
Path-based adaptive weighting of random forest trees via decision path patterns delivers statistically significant accuracy gains on 36 binary classification benchmarks with minimal class-recall regression.