浅析信息理论在决策树分类算法ID3中的应用

Analysis of the Theoretical of Information Used in Decision Tree Classifiers ID3

分类是数据挖掘的重要内容之一,其中决策树分类法在海量数据环境中应用最为广泛,本文论述了决策树分类法ID3算法中的信息熵及其增益原理,并总结了ID3算法引进信息理论后的优点。

Classification is an important problem in data mining, decision tree classifiers have found the widest applicability in large - scale data mining environments. This paper analyzes Entropy and information gain in decision tree ID3 method, advantages after the introduction of information theory are summarized.