Implementation of an Improved ID3 Decision Tree Algorithm in Data Mining System - Jayakameswaraiah, M; Ramakrishna, S (International Journal of Computer Sciences and Engineering, 2014)
Inductive learning is the learning that is based on induction. In inductive learning Decision tree algorithms are very famous. For the appropriate classification of the objects with the given attributes inductive methods use these algorithms basically. 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 ID3ï¿½s 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 ID3ï¿½s shortcoming effectively and get more reasonable and effective rules. The algorithm is implemented in the java language.