Data Mining of Students' Course Selection Based on Currency Rules and Decision Tree

The currency of data can ensure that data is not obsolete and outdated. As one of the important bases for evaluating data quality, it plays an important role in the availability of data. Data currency rules can effectively discriminate the temporal relationship between data sets. The decision tree can availably classify and predict the data, and can test the attribute values very well. In this paper, the currency rules are combined with the C4.5 algorithm in the decision tree, and the improved algorithm is applied to the college elective data in recent years. Through experiments, the algorithm used in this paper can extract the statute rules from the student elective database. According to the currency rules, the college teaching plan can be planned in advance and the curriculum resources can be allocated reasonably.