2017
DOI: 10.1155/2017/4263064
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Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier

Abstract: The k nearest neighbor is one of the most important and simple procedures for data classification task. The kNN, as it is called, requires only two parameters: the number of k and a similarity measure. However, the algorithm has some weaknesses that make it impossible to be used in real problems. Since the algorithm has no model, an exhaustive comparison of the object in classification analysis and all training dataset is necessary. Another weakness is the optimal choice of k parameter when the object analyzed… Show more

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Cited by 6 publications
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References 22 publications
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