Tight combinatorial generalization bounds for threshold conjunction rulesстатья
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Дата последнего поиска статьи во внешних источниках: 26 августа 2016 г.
Аннотация:We propose a combinatorial technique for obtaining tight data dependent generalization bounds based on a splitting and connectivity graph (SC-graph) of the set of classifiers. We apply this approach to a parametric set of conjunctive rules and propose an algorithm for effective SC-bound computation. Experiments on 6 data sets from the UCI ML Repository show that SC-bound helps to learn more reliable rule-based classifiers as compositions of less overfitted rules.