Selective Feature Bagging of one-class classifiers for novelty detection in high-dimensional data-Reference-Cited by-同舟云学术

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Selective Feature Bagging of one-class classifiers for novelty detection in high-dimensional data

Published:2023-04 Issue: Volume:120 Page:105825
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wang Biao,Wang Wenjing,Meng Guanglei,Meng Tiankuo,Song Bin,Wang Yingnan,Guo Yuming,Qiao Zhihua,Mao Zhizhong

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference39 articles.

1. Theoretical foundations and algorithms for outlier ensembles;Aggarwal;ACM Sigkdd Explor. Newsl.,2015

2. Outlier detection for high dimensional data;Aggarwal,2001

3. KEEL: a software tool to assess evolutionary algorithms for data mining problems;Alcalá-Fdez;Soft Comput.,2009

4. Graph-based relevancy-redundancy gene selection method for cancer diagnosis;Azadifar;Comput. Biol. Med.,2022

5. A multi–modal unsupervised fault detection system based on power signals and thermal imaging via deep AutoEncoder neural network;Cordoni;Eng. Appl. Artif. Intell.,2022

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