A Hybrid Two-Stage Teaching-Learning-Based Optimization Algorithm for Feature Selection in Bioinformatics

The "curse of dimensionality" brings new challenges to the feature selection (FS) problem, especially in bioinformatics filed. In this paper, we propose a hybrid Two-Stage Teaching-Learning-Based Optimization (TS-TLBO) algorithm to improve the performance of bioinformatics data classificat...

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Bibliographic Details
Published in:	IEEE/ACM transactions on computational biology and bioinformatics Vol. 20; no. 3; pp. 1746 - 1760
Main Authors:	Kang, Yan, Wang, Haining, Pu, Bin, Tao, Liu, Chen, Jianguo, Yu, Philip S.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Bioinformatics Classification Classification algorithms Clustering algorithms Convergence data classification Education Exploitation Feature extraction Feature selection Humans hybrid search Learning Machine learning Mutation Mutation rates Optimization Performance enhancement Search problems Teachers Teaching teaching–learning-based optimization
ISSN:	1545-5963, 1557-9964, 1557-9964
Online Access:	Get full text
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