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- W1569854597 abstract "We present in this paper a simple, yet valuable improvement to the traditional k-Nearest Neighbor (kNN) classifier. It aims at addressing the issue of unbalanced classes by maximizing the class-wise classification accuracy. The proposed classifier also gives the option of favoring a particular class through evaluating a small set of fuzzy rules. When tested on a number of UCI datasets, the proposed algorithm managed to achieve a uniformly good performance." @default.
- W1569854597 created "2016-06-24" @default.
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- W1569854597 date "2009-01-01" @default.
- W1569854597 modified "2023-09-23" @default.
- W1569854597 title "A MODIFIED K-NEAREST NEIGHBOR CLASSIFIER TO DEAL WITH UNBALANCED CLASSES" @default.
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- W1569854597 doi "https://doi.org/10.5220/0002282604080413" @default.
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