基于标准置换检验的差异序列模式挖掘算法.

To filter out the false positive patterns returned from the discriminative sequential patterns mining methods,this paper proposed a standard permutation method called SP-DSP.This method firstly mined frequent sequential patterns by the GSP algorithm,then eliminated the patterns whose growth rate were less than the threshold.Finally,it used the standard permutation method to compute the p-values of tested patterns.As a result,the number of false positive patterns could be controlled under the multiple hypothesis testing measures.The experiments show that the SP-DSP algorithm can alleviate a lot of false positive patterns and retain as many true patterns as possible,which improves the accuracy of the downstream classification tasks. [ABSTRACT FROM AUTHOR]