Abstract
The paper presents that with the application of \(Z^+\)-numbers arithmetic, the k nearest neighbors method can be adapted to various types of data. Both, the learning data and the input data may be in the form of the crisp number, interval, fuzzy or \(Z^+\)-number. The paper discusses the methods of performing arithmetic operations on uncertain data of various types and explains how to use them in the kNN method. Experiments show that the method works correctly and gives credible results.
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Pluciński, M. (2019). Processing of \(Z^+\)-numbers Using the k Nearest Neighbors Method. In: Pejaś, J., El Fray, I., Hyla, T., Kacprzyk, J. (eds) Advances in Soft and Hard Computing. ACS 2018. Advances in Intelligent Systems and Computing, vol 889. Springer, Cham. https://doi.org/10.1007/978-3-030-03314-9_7
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DOI: https://doi.org/10.1007/978-3-030-03314-9_7
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