Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder

Data overlapping and imbalanced data are significant challenges in data classification. Extreme learning machine auto‐encoding (ELM‐AE) is a feature reduction method that transforms original features into a new set of features capturing essential information in the data. However, ELM‐AE may not effe...

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Bibliographic Details

Published in:	Advanced Intelligent Systems
Main Authors:	Ekkarat Boonchieng, Wanchaloem Nadda
Format:	Article
Language:	English
Published:	Wiley 2025-03-01
Subjects:	auto‐encoding data classification data overlapping extreme learning machine auto‐encoding imbalanced data
Online Access:	https://doi.org/10.1002/aisy.202400255