An adaptive multi-class imbalanced classification framework based on ensemble methods and deep network

Data imbalance is one of the most difficult problems in machine learning. The improved ensemble learning model is a promising solution to mitigate this challenge. In this paper, an improved multi-class imbalanced data classification framework is proposed by combining the Focal Loss with Boosting mod...

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Bibliographic Details

Main Authors:	Xuezheng Jiang, Junyi Wang, Qinggang Meng, Mohamad Saada, Haibin Cai
Format:	Default Article
Published:	2023
Subjects:	Engineering Information and computing sciences Cognitive and computational psychology Multi-class imbalanced classification framework Improved focal loss HAFL-boosting Two-stage classification method
Online Access:	https://hdl.handle.net/2134/22268977.v1
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