JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

Volume 30 Issue 1
January 2015
Article Contents
ZHU Fu-bao, HUO Xiao-qi and XU Xian-jing. Improved ID3 decision tree algorithm based on rough set[J]. Journal of Light Industry, 2015, 30(1): 50-54. doi: 10.3969/j.issn.2095-476X.2015.01.011
Citation: ZHU Fu-bao, HUO Xiao-qi and XU Xian-jing. Improved ID3 decision tree algorithm based on rough set[J]. Journal of Light Industry, 2015, 30(1): 50-54. doi: 10.3969/j.issn.2095-476X.2015.01.011 shu

Improved ID3 decision tree algorithm based on rough set

  • Received Date: 2014-04-01
    Available Online: 2015-01-15
  • The traditional decision tree algorithms such as ID3 usually uses a single attribute as the basis of branching judgment.The scale of the tree generated by ID3 is very large and rules formed are difficult to understand.Aiming at the problems described above, an algorithm was proposed using multi-variable as the judging conditions of node attributes.By using the property of attribute dependency in rough set and choosing nuclear properties of condition attributes relative to decision attributes in the information system as multi-variable node attributes,the algorithm used the concept of relative generalization to aid the branching process and generated a multi-variable decision tree.Through the analysis of example and by comparing with the conventional ID3 algorithm, the high efficiency of the improved algorithm was verified.
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