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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https://hdl.handle.net/2134/22268977.v1

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