Improving the Predictive Performances of k Nearest Neighbors Learning by Efficient Variable Selection
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This paper computationally demonstrates a sharp improvement in predictive performance for k nearest neighbors thanks to an efficient forward selection of the predictor variables. We show both simulated and real-world data that this novel repeatedly approaches outperformance regression models under stepwise selection
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