Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees
Serrurier , Mathieu; Prade , Henri;
Publisher: HAL CCSD
Subject: Intelligence artificielle | [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] | [ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG] | [ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL] | Logique en informatique | Machine learning | [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] | [ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO] | [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO] | Informatique et langage | Decision trees | [ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI] | Apprentissage | [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
International audience; Entropy gain is widely used for learning decision trees. However, as we go deeper downward the tree, the examples become rarer and the faithfulness of entropy decreases. Thus, misleading choices and over-fitting may occur and the tree has to be a... View more
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