EvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks

Feature engineering is an effective method for solving classification problems. Many existing feature engineering studies have focused on image or video data and not on structured data. This study proposes EvaGoNet, which refines the decoder module of the Gaussian mixture variational autoencoder usi...

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Bibliographic Details

Published in:	Information sciences Vol. 629; pp. 109 - 122
Main Authors:	Luo, Changfan, Xu, Yiping, Shao, Yongkang, Wang, Zihan, Hu, Jianzheng, Yuan, Jiawei, Liu, Yuchen, Duan, Meiyu, Huang, Lan, Zhou, Fengfeng
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.06.2023
Subjects:	bioOMIC data EvaGoNet Feature engineering Gaussian mixture VAE VAE WGANgp WGANgp VAE Gaussian mixture VAE Feature engineering bioOMIC data EvaGoNet
ISSN:	0020-0255, 1872-6291
Online Access:	Get full text
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