An Attributes Correlation Based Learning Guidance Model

Using the theory of Web Data Mining, this paper proposes a physics discipline personalized learning evaluation system model based on decision tree algorithm. The overall structure of this system model, which is applied to the network-based education, is presented. The key part of the model, data collection module and personalized evaluation module are introduced. The advantages and disadvantages of the ID3 algorithm and the C4.5 algorithm are analyzed respectively. Taking the comparison of the two algorithms and the unique characteristics of the personalized learning system into consideration, a new_C4.5r decision tree rule simplification algorithm based on attributes correlation is proposed in this paper. The results from a set of experiments shows that the new_C4.5r decision tree algorithm outperforms the previous ones in running time, the size of the rule sets and overhead.