An improved ID3 decision tree algorithm

Decision tree is an important method for both induction research and data mining, which is mainly used for model classification and prediction. ID3 algorithm is the most widely used algorithm in the decision tree so far. Through illustrating on the basic ideas of decision tree in data mining, in thi...

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Bibliographic Details
Main Authors: Chen Jin, Luo De-lin, Mu Fen-xiang
Format: Conference Proceeding
Language:English
Subjects:
association function(AF)
Computer networks
Computer science
Computer science education
Data mining
decision tree
Decision trees
Educational technology
Entropy
ID3
Information science
Predictive models
Testing
variety bias
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Summary:Decision tree is an important method for both induction research and data mining, which is mainly used for model classification and prediction. ID3 algorithm is the most widely used algorithm in the decision tree so far. Through illustrating on the basic ideas of decision tree in data mining, in this paper, the shortcoming of ID3's inclining to choose attributes with many values is discussed, and then a new decision tree algorithm combining ID3 and association function(AF) is presented. The experiment results show that the proposed algorithm can overcome ID3's shortcoming effectively and get more reasonable and effective rules.
DOI:10.1109/ICCSE.2009.5228509