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Optimization Problem of k-NN Classifier for Missing Values Case

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Interval-Valued Methods in Classifications and Decisions

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 378))

Abstract

In this chapter we present a method of dealing with missing values in data sets. This method uses interval-valued fuzzy calculus and we show that it outperforms other methods that were previously known. The obtained results may be useful in diverse computer support systems but especially in the computer support systems devoted to support the medical diagnosis.

You have to teach your algorithm what it can do and what it cannot do because, otherwise, there is a risk that the algorithms will learn the tricks of the old cartels.

Margrethe Vestager

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Authors and Affiliations

  1. Faculty of Mathematics and Natural Sciences, University of Rzeszów, Rzeszów, Poland

    Urszula Bentkowska

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  1. Urszula Bentkowska
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Correspondence to Urszula Bentkowska .

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Bentkowska, U. (2020). Optimization Problem of k-NN Classifier for Missing Values Case. In: Interval-Valued Methods in Classifications and Decisions. Studies in Fuzziness and Soft Computing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-030-12927-9_4

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