Granular Classification for Imbalanced Datasets: A Minkowski Distance-Based Method

The problem of classification for imbalanced datasets is frequently encountered in practical applications. The data to be classified in this problem are skewed, i.e., the samples of one class (the minority class) are much less than those of other classes (the majority class). When dealing with imbal...

書誌詳細
出版年:	Algorithms
主要な著者:	Chen Fu, Jianhua Yang
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2021-02-01
主題:	fuzzy granular classification information granules Minkowski distance imbalanced datasets
オンライン･アクセス:	https://www.mdpi.com/1999-4893/14/2/54

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