Survey on Decision Tree Classification algorithms for the Evaluation of Student Performance

Now days, the amount of data stored in educational database is increasing rapidly. These databases contain hidden information for improvement of student’s performance. Classification of data objects is a data mining and knowledge management technique used in grouping similar data objects together. There are many classification algorithms available in literature but decision tree is the most commonly used because of its ease of implementation and easier to understand compared to other classification algorithms. The ID3, C4.5 and CART decision tree algorithms has been applied on the data of students to predict their performance. In this paper, all the algorithms are explained one by one. Performance and results are compared of all algorithms and evaluation is done by already existing datasets. All the algorithms has a satisfactory performance but accuracy is more witnessed in case of C4.5 algorithm.