Abstract
Desion tree,which is used to classify samples, is one of the important models in data mining. As the core algorithm of decision tree,the classical ID3 algorithm is being widely used in classification problems by its simplicity and efficiency. Unfortunately, it is prone to making the attribute which contains more values as decision attribute, so the attribute which has strong classification ability are probably missed. Proposes an improved ID3 algorithm. When the most information gains of the attributions are same, the algorithm helps us to select an attribute which can get better classification effect. Compared to the classical ID3 algorithm, the new one can reduce misclassification rate and simplify the complexity of the decision tree.
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