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Lecture Notes in Computer Science
This paper proposes a kNN model-based feature selection method aimed at improving the efficiency and effectiveness of the ReliefF method by: (1) using a kNN model as the starter selection, aimed at choosing a set of more meaningful representatives to replace the original data for feature selection; (2) integration of the Heterogeneous Value Difference Metric to handle heterogeneous applications -those with both ordinal and nominal features; and (3) presenting a simple method of differencedoi:10.1007/11551188_44 fatcat:fb6cbh3l6fg43faxnlx432h74m