Improved ID3 Algorithm Based on Intelligent Computer Distance Education

Authors

  • Yunxia Wu School of Continuing Education, Shijiazhuang University of Applied Technology, Shijiazhuang 050081, China
  • Hengjie Zhang Department of Information Engineering, Shijiazhuang University of Applied Technology, Shijiazhuang 050081, China
  • Xin Li Department of Electrical and Electronic Engineering, Shijiazhuang University of Applied Technology, Shijiazhuang 050081, China

Abstract


At present, the distance education application system lacks intelligence, as well as innovation, and cannot provide a personalized teaching method for learners on different levels. After introducing the Iterative Dichotomiser 3 (ID3) algorithm online learners can be classified intelligently according to their inherent characteristics, to achieve targeted teaching for learners of different levels. However, the traditional decision tree ID3 algorithm has the problem of multi-value tendency, and the selection of split attributes does not work with objective facts automatically. A modified factor attribute selection method based on gray association analysis, focusing on an intelligentized target, is used to improve the properties with more values but a lower gray association degree. The sine value of a gray association degree is used as the correction factor to overcome the deficiency of the traditional ID3 algorithm when calculating the information gain of the properties. By introducing the improved ID3 algorithm into the distance education system, learners can be better classified to achieve intelligent learning guidance.

Keywords: ID3 algorithm; decision tree; gray correlation degree; correction factor; distance education system; intelligentized design

Cite As

Y. Wu, H. Zhang, X. Li, “Improved ID3 Algorithm Based on Intelligent Computer Distance Educationâ€, Engineering Intelligent Systems, vol. 28 no. 4, pp. 223-227, 2020.





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Published

2020-12-01

Issue

Vol. 28 No. 4 (2020): International Journal of Engineering Intelligent Systems

Section

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