A recursive tree of logistic regression nodes improves binary classification on a custom augmented wine-quality dataset, but the method largely re-implements hierarchical mixtures of experts.
A Decision Theoretic Generalization of On-Line Learning and an Application to Boosting,
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Dynamic Logistic Ensembles with Recursive Probability and Automatic Subset Splitting for Enhanced Binary Classification
A recursive tree of logistic regression nodes improves binary classification on a custom augmented wine-quality dataset, but the method largely re-implements hierarchical mixtures of experts.