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

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.