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Expediting K-means cluster analysis data mining using subsample elimination preprocessing
Expediting K-means cluster analysis data mining using subsample elimination preprocessing
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机译:使用子样本消除预处理加快K-means聚类分析数据挖掘
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摘要
Improved efficiencies of data mining clustering techniques are provided by preprocessing a sample set of data points taken from a complete data set to provide seeds for centroid calculations of the complete data set. Such seeds are generated by selecting a uniform sample set of data points from a set of multi-dimensional data and then seed values for the cluster determination calculation are determined using a centroid analysis on the sample set of data points. The number of seeds calculated corresponds to a number of data clusters expected in the set of multi-dimensional data points. Seed values are determined using subsample elimination techniques.
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