High-dimensional multi-objective feature selection with niche-based binary differential evolution
•The model for the multi-objective feature selection problem has been established.•A niche-based binary differential evolution algorithm is proposed.•The MONBDE algorithm outperforms the comparison algorithms in terms of performance. Feature selection is a critical step in machine learning and data...
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| Published in: | Expert systems with applications Vol. 298; p. 129478 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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01.03.2026
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| ISSN: | 0957-4174 |
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| Abstract | •The model for the multi-objective feature selection problem has been established.•A niche-based binary differential evolution algorithm is proposed.•The MONBDE algorithm outperforms the comparison algorithms in terms of performance.
Feature selection is a critical step in machine learning and data mining, aiming to identify the most relevant features from a dataset to improve model performance while reducing computational costs. In high-dimensional data, as the dimensionality of data increases rapidly, feature selection faces an enormous search space, limiting the efficiency and effectiveness of traditional methods. To address these challenges, multi-objective optimization algorithms have emerged as a promising strategy for feature selection due to their ability to optimize multiple conflicting objectives simultaneously. We propose a niche-based binary differential evolution algorithm (MONBDE) for high-dimensional multi-objective feature selection. MONBDE enhances feature selection performance through several mechanisms: a niche-based binary differential evolution operator, redundant solution repair mechanism and an environmental selection strategy. In experiments, the proposed algorithm was compared with five advanced multi-objective optimization algorithms and tested on 15 benchmark datasets using three common metrics. Experimental results show that the MONBDE algorithm outperforms comparative algorithms in terms of classification accuracy and feature subset size across most datasets. The proposed strategy effectively eliminates redundant and irrelevant solutions in feature selection, leading to a significant improvement in model classification performance. |
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| AbstractList | •The model for the multi-objective feature selection problem has been established.•A niche-based binary differential evolution algorithm is proposed.•The MONBDE algorithm outperforms the comparison algorithms in terms of performance.
Feature selection is a critical step in machine learning and data mining, aiming to identify the most relevant features from a dataset to improve model performance while reducing computational costs. In high-dimensional data, as the dimensionality of data increases rapidly, feature selection faces an enormous search space, limiting the efficiency and effectiveness of traditional methods. To address these challenges, multi-objective optimization algorithms have emerged as a promising strategy for feature selection due to their ability to optimize multiple conflicting objectives simultaneously. We propose a niche-based binary differential evolution algorithm (MONBDE) for high-dimensional multi-objective feature selection. MONBDE enhances feature selection performance through several mechanisms: a niche-based binary differential evolution operator, redundant solution repair mechanism and an environmental selection strategy. In experiments, the proposed algorithm was compared with five advanced multi-objective optimization algorithms and tested on 15 benchmark datasets using three common metrics. Experimental results show that the MONBDE algorithm outperforms comparative algorithms in terms of classification accuracy and feature subset size across most datasets. The proposed strategy effectively eliminates redundant and irrelevant solutions in feature selection, leading to a significant improvement in model classification performance. |
| ArticleNumber | 129478 |
| Author | Zuo, Xiang Yue, Xuezhi Xiong, Chao Ling, Pengfei Zeng, Yuan Peng, Hu |
| Author_xml | – sequence: 1 givenname: Xuezhi orcidid: 0000-0002-4556-8914 surname: Yue fullname: Yue, Xuezhi email: 764234871@qq.com organization: College of Science, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China – sequence: 2 givenname: Xiang surname: Zuo fullname: Zuo, Xiang organization: College of Science, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China – sequence: 3 givenname: Pengfei surname: Ling fullname: Ling, Pengfei organization: College of Science, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China – sequence: 4 givenname: Chao surname: Xiong fullname: Xiong, Chao organization: College of Science, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China – sequence: 5 givenname: Hu surname: Peng fullname: Peng, Hu organization: School of Computer and Big Data Science, Jiujiang University, Jiujiang, 332005, Jiangxi, China – sequence: 6 givenname: Yuan surname: Zeng fullname: Zeng, Yuan organization: Institute of Mechanical and Electrical Engineering, Guangdong Communication Polytechnic, Qingyuan, 511500, Guangdong, China |
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| Cites_doi | 10.1109/TCYB.2022.3218345 10.1109/TEVC.2022.3168052 10.1109/78.738245 10.1109/TEVC.2019.2918140 10.1016/j.knosys.2023.110801 10.1016/j.neucom.2022.04.083 10.1016/j.ins.2019.08.040 10.1016/j.knosys.2022.108582 10.1109/TEVC.2018.2866854 10.1109/TCYB.2024.3372070 10.1007/s00521-022-07407-x 10.1016/0167-8655(94)90127-9 10.1016/j.asoc.2023.110765 10.1109/TEVC.2007.892759 10.1023/A:1008202821328 10.1016/j.asoc.2013.09.018 10.1007/s12293-022-00354-z 10.1016/j.ins.2024.120269 10.1016/j.knosys.2023.110361 10.1007/s40747-023-01177-2 10.1109/TCYB.2022.3213236 10.1109/MCI.2017.2742868 10.1142/S1469026814500096 10.1016/j.knosys.2022.108640 10.1109/4235.996017 10.1016/j.knosys.2021.106966 10.1016/j.ins.2017.09.028 10.1016/j.eswa.2009.03.032 10.1109/TCYB.2019.2927780 10.1109/TEVC.2020.3016049 |
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| References | Paul, Jain, Saha, Mathew (bib0015) 2021; 222 Deb, Pratap, Agarwal, Meyarivan (bib0003) 2002; 6 Pan, Liu, Chu (bib0014) 2022; 245 Xue, Cervante, Shang, Browne, Zhang (bib0026) 2014; 13 Zhao, Zhan, Lin, Chen, Luo, Zhang, Zhang (bib0030) 2019; 50 Reeves, Zhe (bib0018) 1999; 47 Tian, Cheng, Zhang, Jin (bib0020) 2017; 12 Tian, Zhang, Wang, Jin (bib0022) 2019; 24 Hancer (bib0007) 2022; 34 Xue, Zhang, Browne (bib0027) 2014; 18 Agrawal, Tiwari, Yaduvanshi, Rajak (bib0001) 2023; 265 Jiao, Xue, Zhang (bib0009) 2022; 53 Hancer, Xue, Zhang, Karaboga, Akay (bib0008) 2018; 422 Luo, Zhou, Jiang, Ma (bib0013) 2022; 14 Deng, Li, Wang, Cao, Li (bib0004) 2023; 148 Rashno, Shafipour, Fadaei (bib0017) 2022; 245 Pudil, Novovičová, Kittler (bib0016) 1994; 15 Han, Peng, Mei, Cao, Deng, Wang, Wu (bib0006) 2023; 277 Zhang, Gong, Gao, Tian, Sun (bib0029) 2020; 507 Tian, Cheng, Zhang, Su, Jin (bib0021) 2018; 23 Zhou, Yang, Huang, Lee, Kwong (bib0031) 2024; 54 Dokeroglu, Deniz, Kiziloz (bib0005) 2022; 494 Li, Ma, Lv, Wang, Deng (bib0011) 2024; 663 Chu, Zhuang, Pan, Mohamed, Hu (bib0002) 2024; 10 Li, Zhang, Zeng (bib0012) 2009; 36 Storn, Price (bib0019) 1997; 11 Xu, Xue, Zhang (bib0025) 2020; 25 Zhang, Li (bib0028) 2007; 11 Wang, Xue, Liang, Zhang (bib0023) 2022; 27 Kong, Gao, OuYang, Ge (bib0010) 2014; 35 Wang, Xue, Liang, Zhang (bib0024) 2022; 53 Zhang (10.1016/j.eswa.2025.129478_bib0028) 2007; 11 Zhang (10.1016/j.eswa.2025.129478_bib0029) 2020; 507 Zhou (10.1016/j.eswa.2025.129478_bib0031) 2024; 54 Chu (10.1016/j.eswa.2025.129478_bib0002) 2024; 10 Tian (10.1016/j.eswa.2025.129478_bib0021) 2018; 23 Pan (10.1016/j.eswa.2025.129478_bib0014) 2022; 245 Pudil (10.1016/j.eswa.2025.129478_bib0016) 1994; 15 Kong (10.1016/j.eswa.2025.129478_bib0010) 2014; 35 Tian (10.1016/j.eswa.2025.129478_bib0020) 2017; 12 Tian (10.1016/j.eswa.2025.129478_bib0022) 2019; 24 Storn (10.1016/j.eswa.2025.129478_bib0019) 1997; 11 Xue (10.1016/j.eswa.2025.129478_bib0027) 2014; 18 Han (10.1016/j.eswa.2025.129478_bib0006) 2023; 277 Li (10.1016/j.eswa.2025.129478_bib0012) 2009; 36 Li (10.1016/j.eswa.2025.129478_bib0011) 2024; 663 Paul (10.1016/j.eswa.2025.129478_bib0015) 2021; 222 Agrawal (10.1016/j.eswa.2025.129478_bib0001) 2023; 265 Xu (10.1016/j.eswa.2025.129478_bib0025) 2020; 25 Deb (10.1016/j.eswa.2025.129478_bib0003) 2002; 6 Hancer (10.1016/j.eswa.2025.129478_bib0008) 2018; 422 Rashno (10.1016/j.eswa.2025.129478_bib0017) 2022; 245 Deng (10.1016/j.eswa.2025.129478_bib0004) 2023; 148 Zhao (10.1016/j.eswa.2025.129478_bib0030) 2019; 50 Reeves (10.1016/j.eswa.2025.129478_bib0018) 1999; 47 Wang (10.1016/j.eswa.2025.129478_bib0023) 2022; 27 Xue (10.1016/j.eswa.2025.129478_bib0026) 2014; 13 Wang (10.1016/j.eswa.2025.129478_bib0024) 2022; 53 Luo (10.1016/j.eswa.2025.129478_bib0013) 2022; 14 Dokeroglu (10.1016/j.eswa.2025.129478_bib0005) 2022; 494 Hancer (10.1016/j.eswa.2025.129478_bib0007) 2022; 34 Jiao (10.1016/j.eswa.2025.129478_bib0009) 2022; 53 |
| References_xml | – volume: 53 start-page: 6676 year: 2022 end-page: 6689 ident: bib0024 article-title: Differential evolution with duplication analysis for feature selection in classification publication-title: IEEE Transactions on Cybernetics – volume: 265 year: 2023 ident: bib0001 article-title: Feature subset selection using multimodal multiobjective differential evolution publication-title: Knowledge-Based Systems – volume: 10 start-page: 485 year: 2024 end-page: 507 ident: bib0002 article-title: Enhanced sparseEA for large-scale multi-objective feature selection problems publication-title: Complex & Intelligent Systems – volume: 47 start-page: 123 year: 1999 end-page: 132 ident: bib0018 article-title: Sequential algorithms for observation selection publication-title: IEEE Transactions on Signal Processing – volume: 14 start-page: 77 year: 2022 end-page: 93 ident: bib0013 article-title: A particle swarm optimization based multiobjective memetic algorithm for high-dimensional feature selection publication-title: Memetic Computing – volume: 23 start-page: 331 year: 2018 end-page: 345 ident: bib0021 article-title: A strengthened dominance relation considering convergence and diversity for evolutionary many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: bib0003 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Transactions on Evolutionary Computation – volume: 27 start-page: 296 year: 2022 end-page: 310 ident: bib0023 article-title: Differential evolution-based feature selection: A niching-based multiobjective approach publication-title: IEEE Transactions on Evolutionary Computation – volume: 50 start-page: 3343 year: 2019 end-page: 3357 ident: bib0030 article-title: Local binary pattern-based adaptive differential evolution for multimodal optimization problems publication-title: IEEE Transactions on Cybernetics – volume: 13 year: 2014 ident: bib0026 article-title: Binary PSO and rough set theory for feature selection: A multi-objective filter based approach publication-title: International Journal of Computational Intelligence and Applications – volume: 15 start-page: 1119 year: 1994 end-page: 1125 ident: bib0016 article-title: Floating search methods in feature selection publication-title: Pattern Recognition Letters – volume: 422 start-page: 462 year: 2018 end-page: 479 ident: bib0008 article-title: Pareto front feature selection based on artificial bee colony optimization publication-title: Information Sciences – volume: 222 year: 2021 ident: bib0015 article-title: Multi-objective PSO based online feature selection for multi-label classification publication-title: Knowledge-Based Systems – volume: 494 start-page: 269 year: 2022 end-page: 296 ident: bib0005 article-title: A comprehensive survey on recent metaheuristics for feature selection publication-title: Neurocomputing – volume: 24 start-page: 380 year: 2019 end-page: 393 ident: bib0022 article-title: An evolutionary algorithm for large-scale sparse multiobjective optimization problems publication-title: IEEE Transactions on Evolutionary Computation – volume: 25 start-page: 205 year: 2020 end-page: 218 ident: bib0025 article-title: A duplication analysis-based evolutionary algorithm for biobjective feature selection publication-title: IEEE Transactions on Evolutionary Computation – volume: 18 start-page: 261 year: 2014 end-page: 276 ident: bib0027 article-title: Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms publication-title: Applied Soft Computing – volume: 148 year: 2023 ident: bib0004 article-title: A feature-thresholds guided genetic algorithm based on a multi-objective feature scoring method for high-dimensional feature selection publication-title: Applied Soft Computing – volume: 36 start-page: 11570 year: 2009 end-page: 11581 ident: bib0012 article-title: Research of multi-population agent genetic algorithm for feature selection publication-title: Expert Systems with Applications – volume: 34 start-page: 17523 year: 2022 end-page: 17537 ident: bib0007 article-title: A multi-objective artificial bee colony algorithm for cost-sensitive subset selection publication-title: Neural Computing and Applications – volume: 245 year: 2022 ident: bib0017 article-title: Particle ranking: An efficient method for multi-objective particle swarm optimization feature selection publication-title: Knowledge-Based Systems – volume: 245 year: 2022 ident: bib0014 article-title: A competitive mechanism based multi-objective differential evolution algorithm and its application in feature selection publication-title: Knowledge-Based Systems – volume: 11 start-page: 341 year: 1997 end-page: 359 ident: bib0019 article-title: Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces publication-title: Journal of Global Optimization – volume: 663 year: 2024 ident: bib0011 article-title: Enhanced NSGA-II-based feature selection method for high-dimensional classification publication-title: Information sciences – volume: 35 start-page: 484 year: 2014 end-page: 488 ident: bib0010 article-title: Binary differential evolution algorithm without parameter variation publication-title: Journal of Northeastern University(Natural Science) – volume: 54 start-page: 5205 year: 2024 end-page: 5216 ident: bib0031 article-title: A novel multiobjective genetic programming approach to high-dimensional data classification publication-title: IEEE Transactions on Cybernetics – volume: 12 start-page: 73 year: 2017 end-page: 87 ident: bib0020 article-title: PlatEMO: A MATLAB platform for evolutionary multi-objective optimization [educational forum] publication-title: IEEE Computational Intelligence Magazine – volume: 507 start-page: 67 year: 2020 end-page: 85 ident: bib0029 article-title: Binary differential evolution with self-learning for multi-objective feature selection publication-title: Information Sciences – volume: 277 year: 2023 ident: bib0006 article-title: Multi-strategy multi-objective differential evolutionary algorithm with reinforcement learning publication-title: Knowledge-Based Systems – volume: 11 start-page: 712 year: 2007 end-page: 731 ident: bib0028 article-title: Moea/d: A multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Transactions on Evolutionary Computation – volume: 53 start-page: 7773 year: 2022 end-page: 7786 ident: bib0009 article-title: Benefiting from single-objective feature selection to multiobjective feature selection: A multiform approach publication-title: IEEE Transactions on Cybernetics – volume: 53 start-page: 7773 issue: 12 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0009 article-title: Benefiting from single-objective feature selection to multiobjective feature selection: A multiform approach publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2022.3218345 – volume: 27 start-page: 296 issue: 2 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0023 article-title: Differential evolution-based feature selection: A niching-based multiobjective approach publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2022.3168052 – volume: 47 start-page: 123 issue: 1 year: 1999 ident: 10.1016/j.eswa.2025.129478_bib0018 article-title: Sequential algorithms for observation selection publication-title: IEEE Transactions on Signal Processing doi: 10.1109/78.738245 – volume: 24 start-page: 380 issue: 2 year: 2019 ident: 10.1016/j.eswa.2025.129478_bib0022 article-title: An evolutionary algorithm for large-scale sparse multiobjective optimization problems publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2019.2918140 – volume: 277 year: 2023 ident: 10.1016/j.eswa.2025.129478_bib0006 article-title: Multi-strategy multi-objective differential evolutionary algorithm with reinforcement learning publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2023.110801 – volume: 494 start-page: 269 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0005 article-title: A comprehensive survey on recent metaheuristics for feature selection publication-title: Neurocomputing doi: 10.1016/j.neucom.2022.04.083 – volume: 507 start-page: 67 year: 2020 ident: 10.1016/j.eswa.2025.129478_bib0029 article-title: Binary differential evolution with self-learning for multi-objective feature selection publication-title: Information Sciences doi: 10.1016/j.ins.2019.08.040 – volume: 245 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0014 article-title: A competitive mechanism based multi-objective differential evolution algorithm and its application in feature selection publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2022.108582 – volume: 23 start-page: 331 issue: 2 year: 2018 ident: 10.1016/j.eswa.2025.129478_bib0021 article-title: A strengthened dominance relation considering convergence and diversity for evolutionary many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2018.2866854 – volume: 54 start-page: 5205 issue: 9 year: 2024 ident: 10.1016/j.eswa.2025.129478_bib0031 article-title: A novel multiobjective genetic programming approach to high-dimensional data classification publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2024.3372070 – volume: 34 start-page: 17523 issue: 20 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0007 article-title: A multi-objective artificial bee colony algorithm for cost-sensitive subset selection publication-title: Neural Computing and Applications doi: 10.1007/s00521-022-07407-x – volume: 15 start-page: 1119 issue: 11 year: 1994 ident: 10.1016/j.eswa.2025.129478_bib0016 article-title: Floating search methods in feature selection publication-title: Pattern Recognition Letters doi: 10.1016/0167-8655(94)90127-9 – volume: 148 year: 2023 ident: 10.1016/j.eswa.2025.129478_bib0004 article-title: A feature-thresholds guided genetic algorithm based on a multi-objective feature scoring method for high-dimensional feature selection publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2023.110765 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 10.1016/j.eswa.2025.129478_bib0028 article-title: Moea/d: A multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2007.892759 – volume: 11 start-page: 341 year: 1997 ident: 10.1016/j.eswa.2025.129478_bib0019 article-title: Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces publication-title: Journal of Global Optimization doi: 10.1023/A:1008202821328 – volume: 18 start-page: 261 year: 2014 ident: 10.1016/j.eswa.2025.129478_bib0027 article-title: Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2013.09.018 – volume: 14 start-page: 77 issue: 1 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0013 article-title: A particle swarm optimization based multiobjective memetic algorithm for high-dimensional feature selection publication-title: Memetic Computing doi: 10.1007/s12293-022-00354-z – volume: 663 year: 2024 ident: 10.1016/j.eswa.2025.129478_bib0011 article-title: Enhanced NSGA-II-based feature selection method for high-dimensional classification publication-title: Information sciences doi: 10.1016/j.ins.2024.120269 – volume: 265 year: 2023 ident: 10.1016/j.eswa.2025.129478_bib0001 article-title: Feature subset selection using multimodal multiobjective differential evolution publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2023.110361 – volume: 10 start-page: 485 issue: 1 year: 2024 ident: 10.1016/j.eswa.2025.129478_bib0002 article-title: Enhanced sparseEA for large-scale multi-objective feature selection problems publication-title: Complex & Intelligent Systems doi: 10.1007/s40747-023-01177-2 – volume: 53 start-page: 6676 issue: 10 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0024 article-title: Differential evolution with duplication analysis for feature selection in classification publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2022.3213236 – volume: 12 start-page: 73 issue: 4 year: 2017 ident: 10.1016/j.eswa.2025.129478_bib0020 article-title: PlatEMO: A MATLAB platform for evolutionary multi-objective optimization [educational forum] publication-title: IEEE Computational Intelligence Magazine doi: 10.1109/MCI.2017.2742868 – volume: 13 issue: 02 year: 2014 ident: 10.1016/j.eswa.2025.129478_bib0026 article-title: Binary PSO and rough set theory for feature selection: A multi-objective filter based approach publication-title: International Journal of Computational Intelligence and Applications doi: 10.1142/S1469026814500096 – volume: 35 start-page: 484 issue: 4 year: 2014 ident: 10.1016/j.eswa.2025.129478_bib0010 article-title: Binary differential evolution algorithm without parameter variation publication-title: Journal of Northeastern University(Natural Science) – volume: 245 year: 2022 ident: 10.1016/j.eswa.2025.129478_bib0017 article-title: Particle ranking: An efficient method for multi-objective particle swarm optimization feature selection publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2022.108640 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.eswa.2025.129478_bib0003 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.996017 – volume: 222 year: 2021 ident: 10.1016/j.eswa.2025.129478_bib0015 article-title: Multi-objective PSO based online feature selection for multi-label classification publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2021.106966 – volume: 422 start-page: 462 year: 2018 ident: 10.1016/j.eswa.2025.129478_bib0008 article-title: Pareto front feature selection based on artificial bee colony optimization publication-title: Information Sciences doi: 10.1016/j.ins.2017.09.028 – volume: 36 start-page: 11570 issue: 9 year: 2009 ident: 10.1016/j.eswa.2025.129478_bib0012 article-title: Research of multi-population agent genetic algorithm for feature selection publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2009.03.032 – volume: 50 start-page: 3343 issue: 7 year: 2019 ident: 10.1016/j.eswa.2025.129478_bib0030 article-title: Local binary pattern-based adaptive differential evolution for multimodal optimization problems publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2019.2927780 – volume: 25 start-page: 205 issue: 2 year: 2020 ident: 10.1016/j.eswa.2025.129478_bib0025 article-title: A duplication analysis-based evolutionary algorithm for biobjective feature selection publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2020.3016049 |
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| SubjectTerms | Differential evolution Feature selection Multi-objective optimization Redundant solution repair |
| Title | High-dimensional multi-objective feature selection with niche-based binary differential evolution |
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