imbalance

Class imbalance usually damages the performance of classifiers. Thus, it is important to treat data before applying a classifier algorithm. This package includes recent resampling algorithms in the literature: (Barua et al. 2014) doi:10.1109/tkde.2012.232; (Das et al. 2015) doi:10.1109/tkde.2014.2324567, (Zhang et al. 2014) doi:10.1016/j.inffus.2013.12.003; (Gao et al. 2014) doi:10.1016/j.neucom.2014.02.006; (Almogahed et al. 2014) doi:10.1007/s00500-014-1484-5. It also includes an useful interface to perform oversampling.