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

被引：138

作者：

Zhang, Chongsheng ^{[1
]}

Bi, Jingjun ^{[1
]}

Xu, Shixin ^{[1
]}

Ramentol, Enislay ^{[2
]}

Fan, Gaojuan ^{[1
]}

Qiao, Baojun ^{[1
]}

Fujita, Hamido ^{[3
,4
]}

机构：

[1] Henan Univ, Big Data Res Ctr, Kaifeng 475001, Peoples R China

[2] SICS Swedish ICT, Isafjordsgatan 22,Box 1263, SE-16429 Kista, Sweden

[3] Ho Chi Minh City Univ Technol HUTECH, Fac Informat Technol, Ho Chi Minh City, Vietnam

[4] Iwate Prefectural Univ, Fac Software & Informat Sci, Takizawa, Iwate 0200693, Japan

来源：

KNOWLEDGE-BASED SYSTEMS | 2019年 / 174卷

关键词：

Multi-class imbalance leaning; Imbalanced data classification; PARAMETERIZATION; CLASSIFICATION; DOMAIN;

D O I：

10.1016/j.knosys.2019.03.001

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：137 / 143

页数：7

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