RIONIDA: A Novel Algorithm for Imbalanced Data Combining Instance-Based Learning and Rule Induction

被引：0
作者：
Gora, Grzegorz [1 ]
Skowron, Andrzej [2 ]
机构：
[1] Univ Warsaw, Stefana Banacha 2, PL-02097 Warsaw, Poland
[2] PAS, Syst Res Inst, Newelska 6, PL-01447 Warsaw, Poland
来源：
ROUGH SETS, PT I, IJCRS 2024 | 2024年 / 14839卷
关键词：
Imbalanced Learning; Classification; Supervised Learning; Instance-based Learning; k Nearest Neighbours; Rule Induction;
D O I：
10.1007/978-3-031-65665-1_13
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The article presents the RIONIDA learning algorithm based on combination of two widely-used empirical approaches: rule induction and instance-based learning for imbalanced data classification. The algorithm is a substantial extension of the well-known RIONA algorithm developed for balanced data. RIONIDA is relatively fast and significantly outperforms the state-of-the-art algorithms analysed in the paper.
引用
收藏
页码：201 / 219
页数：19
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