Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees
Serrurier, Mathieu; Prade, Henri;
Publisher: HAL CCSD
Subject: [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO] | [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] | Decision trees | Machine learning | [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] | [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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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