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Multi-Imbalance: An open-source software for multi-class imbalance learning

Authors :
Zhang, Chongsheng
Bi, Jingjun
Xu, Shixin
Enislay Ramentol
Fan, Gaojuan
Qiao, Baojun
Fujita, Hamido
Publica
Publication Year :
2019

Abstract

Imbalance classification is one of the most challenging research problems in machine learning. Techniques for two-class imbalance classification are relatively mature nowadays, yet multi-class imbalance learning is still an open problem. Moreover, the community lacks a suitable software tool that can integrate the major works in the field. In this paper, we present Multi-Imbalance, an open source software package for multi-class imbalanced data classification. It provides users with seven different categories of multi-class imbalance learning algorithms, including the latest advances in the field. The source codes and documentations for Multi-Imbalance are publicly available at https://github.com/chongshengzhang/Multi_Imbalance.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.od.......610..867d6c87d8d0d18627161412ec20dc9f