Abstract

In recent years, the school enrollment scale has expanded explosively, and massive student information data sets have brought a lot of troubles to student information management decision-making. Data mining, especially the continuous optimization of decision tree classification algorithms, can effectively manage student data. Therefore, the study of student information management decision system based on decision tree classification algorithm has practical significance. This paper calculates the decision support degree for attributes that are not easily distinguished, and optimizes the decision tree classification algorithm. This article will introduce the modules of student registration management, student status management, examination management and so on in the optimized decision tree classification algorithm application system. In order to verify the feasibility of the system, this article tested and used the basic functions of the system. The test results show that when the number of concurrent users is 100, the actual response time of the system is 0.43s; when the number of concurrent users is 600, the actual response time of the system is 1.56s, which is less than 2s, which verifies that the system functions have reached the expected use effect.

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