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Balanced Neighborhood Classifiers for Imbalanced Data Sets Shunzhi ZHU Ying MA Weiwei PAN Xiatian ZHU Guangchun LUO Publication IEICE TRANSACTIONS on Information and Systems Vol.E97-D No.12 pp.3226-3229 Publication Date: 2014/12/01 Online ISSN: 1745-1361 DOI: 10.1587/transinf.2014EDL8064 Type of Manuscript: LETTER Category: Pattern Recognition Keyword: machine learning, class imbalance, class distribution, classification, Full Text: PDF(546.1KB)>>
Summary: A Balanced Neighborhood Classifier (BNEC) is proposed for class imbalanced data. This method is not only well positioned to capture the class distribution information, but also has the good merits of high-fitting-performance and simplicity. Experiments on both synthetic and real data sets show its effectiveness. | ||||||||||
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