Abstract: Considering the low accuracy of the stream-data classification hasn't high accuracy and compression rate for data mining,the stream-data parallel classification compression algorithm was proposed based on granular analysis and storage of GEP in order to achieve faster parallel classification compression algorithm of streaming data.Firstly,get the least set of stream-data with the granular analysis method,and the approximate granular space according to division rules.Secondly,establish corresponding GEP classification model for different stream-data;Finally,send the data to compression model of GEP and compression data with dynamic storage record set form,extend serial algorithm to the parallel algorithm in MPI+OpenMP hybrid programming model,and verify the algorithm performance with the UCI data and communications bill.The experimental result shows that the effect of the classification compressions time-consuming and the compression ratio are satisfactory,the student's communication bill time-consuming is about 96 s,and the compression ratio can be achieved to 1/3.

Key words: classification compression, granular analysis, GEP, parallel algorithm