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We study an important problem of similarity grouping processing on stream data that inherently contain uncertainty. Method: In this paper SBSP -[Stage by Stage Pruning] a novel pruning method is proposed for fast, accurate clustering and classifying the data where the two stages were grouped into a single framework MYFRAME. Findings: The proposed approach group the data-by-data level pruning using Manhattan distance in first stage. In the second stage, the data is grouped by object leveldoi:10.17485/ijst/2016/v9i8/87969 fatcat:7kpmpkmmbzf7peryoanoev6vbu