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- W1756189466 abstract "One of the most popular techniques in pattern recognition applications is the nearest neighbours (K-NN) classification rule based on the Euclidean distance function. This rule can be modified by data transformations. Variety of distance functions can be induced from data sets in this way. We take into considerations inducing distance functions by linear data transformations. The results of our experiments show the possibility of improving K-NN rules through such transformations." @default.
- W1756189466 created "2016-06-24" @default.
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- W1756189466 date "2004-01-01" @default.
- W1756189466 modified "2023-09-23" @default.
- W1756189466 title "Improving the K-NN Classification with the Euclidean Distance Through Linear Data Transformations" @default.
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- W1756189466 doi "https://doi.org/10.1007/978-3-540-30185-1_3" @default.
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