An Improved ID3 Decision Tree Algorithm

Xiao Juan Chen; Zhi Gang Zhang; Yue Tong

doi:10.4028/www.scientific.net/AMR.962-965.2842

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 962-965An Improved ID3 Decision Tree Algorithm

An Improved ID3 Decision Tree Algorithm

Abstract:

As the classical algorithm of the decision tree classification algorithm, ID3 algorithm is famous for the merits of high classifying speed, strong learning ability and easy construction. But when used to make classification, the problem of inclining to choose attributions which have many values affect its practicality. This paper presents an improved algorithm based on the expectation information entropy and Association Function instead of the traditional information gain. In the improved algorithm, it modified the expectation information entropy with the improved Association Function and the number of the attributes values. The experiment result shows that the improved algorithm can get more reasonable and more effective rules.

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Periodical:

Advanced Materials Research (Volumes 962-965)

Pages:

2842-2847

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.962-965.2842

Citation:

Cite this paper

Online since:

June 2014

Authors:

Xiao Juan Chen*, Zhi Gang Zhang, Yue Tong

Keywords:

Decision Trees, Expectation Information Entropy, ID3 Algorithm, Information Gain

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* - Corresponding Author

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