Discipline Decision Tree Classification Algorithm and Application based on Weighted Information Gain Ratio

Yan Xia, Jian Shu, Na Xu, Hui Feng

2016

Abstract

Discipline evaluation is an important part in higher education evaluation. It plays a significant role in discipline construction in universities and colleges. It is challenging how to use scientific discipline evaluation to classify disciplines, such as advantageous disciplines and newly-emerging ones. This paper proposes an algorithm of discipline decision tree classification based on weighted information gain ratio. It determines evaluation attributes and creates decision tree according to weighted information gain ratio. Discipline classification rules are deduced by decision tree. An automatic classification system is developed, implementing the algorithm and analysing data from universities and colleges in Shanghai. Experimental results show that our scheme can achieve about 83.33% accuracy in forecasts. It provides advice and guidance for discipline evaluation, and establishes foundation for discipline development strategy.

Paper Citation

in Harvard Style

Xia Y., Shu J., Xu N. and Feng H. (2016). Discipline Decision Tree Classification Algorithm and Application based on Weighted Information Gain Ratio . In Proceedings of the 8th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-179-3, pages 77-84. DOI: 10.5220/0005748000770084

in Bibtex Style

@conference{csedu16,
author={Yan Xia and Jian Shu and Na Xu and Hui Feng},
title={Discipline Decision Tree Classification Algorithm and Application based on Weighted Information Gain Ratio},
booktitle={Proceedings of the 8th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2016},
pages={77-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005748000770084},
isbn={978-989-758-179-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - Discipline Decision Tree Classification Algorithm and Application based on Weighted Information Gain Ratio
SN - 978-989-758-179-3
AU - Xia Y.
AU - Shu J.
AU - Xu N.
AU - Feng H.
PY - 2016
SP - 77
EP - 84
DO - 10.5220/0005748000770084