Balanced Neighborhood Classifiers for imbalanced data sets

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Abstract

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 highfitting-performance and simplicity. Experiments on both synthetic and real data sets show its effectiveness.

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APA

Zhu, S., Ma, Y., Pan, W., Zhu, X., & Luo, G. (2014). Balanced Neighborhood Classifiers for imbalanced data sets. In IEICE Transactions on Information and Systems (Vol. E97D, pp. 3226–3229). Maruzen Co., Ltd. https://doi.org/10.1587/transinf.2014EDL8064

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