Aiming at problem of C4. 5 algorithm such as huge amount of logarithm operations

irrelevant attributes interference and attribute correlation effect

propose C4. 5 algorithm based on attribute dependency calculation and PCA. There are some enhancement strategies which includes simplified calculation formula according to principle of equivalent infinitesimal

deal with problem of attribute correlation through calculation of the dependency for attribute and reference the compression principle of principal component analysis（ PCA） algorithm. While introduce two new concepts

"average volatility"and"application weight"to get a new metric of attribute selection. With the evaluation work of the students’ comprehensive performance for application analysis

and use UCI data sets to compare performance. Experimental results show that the improved algorithm evaluation results are more scientific

more accurate and higher computing efficiency than before.