Dynamic Data Stream Multiple Imputation is divided into m equal-sized segments of s transÂactions, and processes the Imputation/update of data stream incrementally in a segment-based manner. HMI uses the simplified Hoeffdingâ€™s bound concepts to calculate the appropriate data stream size for the mining of Missing Data. It then uses the comparison of the two data stream sub-range observations and the Data counts when a segment occurs within the data stream and then adjusts the data stream size appropriately. In this paper implications of HMI algorithm is analysed with Segment time comparison between HMI and FIDS using statlog data set
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