Using representative-based clustering for nearest neighbor dataset editing

Abstract

The goal of dataset editing in instance-based learning is to remove objects from a training set in order to increase the accuracy of a classifier. For example, Wilson editing removes training examples that are misclassified by a nearest neighbor classifier so as to smooth the shape of the resulting decision boundaries. This paper revolves around the use of… (More)
DOI: 10.1109/ICDM.2004.10044

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