Addressing imbalanced classification with instance generation techniques: IPADE-ID

Abstract

A wide number of real word applications presents a class distribution where examples belonging to one class heavily outnumber the examples in the other class. This is an arduous situation where standard classification techniques usually decrease their performance, creating a handicap to correctly identify the minority class, which is precisely the case… (More)
DOI: 10.1016/j.neucom.2013.01.050

Topics

14 Figures and Tables

Cite this paper

@article{Lpez2014AddressingIC, title={Addressing imbalanced classification with instance generation techniques: IPADE-ID}, author={Victoria L{\'o}pez and Isaac Triguero and Crist{\'o}bal J. Carmona and Salvador Garc{\'i}a and Francisco Herrera}, journal={Neurocomputing}, year={2014}, volume={126}, pages={15-28} }