Journal
KNOWLEDGE-BASED SYSTEMS
Volume 174, Issue -, Pages 137-143Publisher
ELSEVIER
DOI: 10.1016/j.knosys.2019.03.001
Keywords
Multi-class imbalance leaning; Imbalanced data classification
Categories
Funding
- European Research Consortium for Informatics and Mathematics (ERCIM), France Alain Bensoussan Fellowship Programme
Ask authors/readers for more resources
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. (C) 2019 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available