Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313291217> ?p ?o ?g. }
- W4313291217 endingPage "1017" @default.
- W4313291217 startingPage "1004" @default.
- W4313291217 abstract "Feature selection, which aims to improve the classification accuracy and reduce the size of the selected feature subset, is an important but challenging optimization problem in data mining. Particle swarm optimization (PSO) has shown promising performance in tackling feature selection problems, but still faces challenges in dealing with large-scale feature selection in Big Data environment because of the large search space. Hence, this paper proposes a bi-directional feature fixation (BDFF) framework for PSO and provides a novel idea to reduce the search space in large-scale feature selection. BDFF uses two opposite search directions to guide particles to adequately search for feature subsets with different sizes. Based on the two different search directions, BDFF can fix the selection states of some features and then focus on the others when updating particles, thus narrowing the large search space. Besides, a self-adaptive strategy is designed to help the swarm concentrate on a more promising direction for search in different stages of evolution and achieve a balance between exploration and exploitation. Experimental results on 12 widely-used public datasets show that BDFF can improve the performance of PSO on large-scale feature selection and obtain smaller feature subsets with higher classification accuracy." @default.
- W4313291217 created "2023-01-06" @default.
- W4313291217 creator A5014921188 @default.
- W4313291217 creator A5029072443 @default.
- W4313291217 creator A5029344996 @default.
- W4313291217 creator A5033098099 @default.
- W4313291217 creator A5056949686 @default.
- W4313291217 creator A5063205295 @default.
- W4313291217 creator A5076869167 @default.
- W4313291217 creator A5084148795 @default.
- W4313291217 date "2023-06-01" @default.
- W4313291217 modified "2023-10-16" @default.
- W4313291217 title "Bi-Directional Feature Fixation-Based Particle Swarm Optimization for Large-Scale Feature Selection" @default.
- W4313291217 cites W1500895378 @default.
- W4313291217 cites W1543715688 @default.
- W4313291217 cites W1981883771 @default.
- W4313291217 cites W1992913497 @default.
- W4313291217 cites W1995972800 @default.
- W4313291217 cites W2017337590 @default.
- W4313291217 cites W2043772506 @default.
- W4313291217 cites W2056423657 @default.
- W4313291217 cites W2075779886 @default.
- W4313291217 cites W2125213524 @default.
- W4313291217 cites W2127931254 @default.
- W4313291217 cites W2152195021 @default.
- W4313291217 cites W2167101736 @default.
- W4313291217 cites W2343420905 @default.
- W4313291217 cites W2489159973 @default.
- W4313291217 cites W2528103328 @default.
- W4313291217 cites W2639370877 @default.
- W4313291217 cites W2767639095 @default.
- W4313291217 cites W2890843359 @default.
- W4313291217 cites W2973261831 @default.
- W4313291217 cites W2973941913 @default.
- W4313291217 cites W2979736100 @default.
- W4313291217 cites W2981943969 @default.
- W4313291217 cites W2987248529 @default.
- W4313291217 cites W2997199851 @default.
- W4313291217 cites W2997412521 @default.
- W4313291217 cites W2997585558 @default.
- W4313291217 cites W3001998614 @default.
- W4313291217 cites W3004565805 @default.
- W4313291217 cites W3012446350 @default.
- W4313291217 cites W3044063956 @default.
- W4313291217 cites W3048904406 @default.
- W4313291217 cites W3086548118 @default.
- W4313291217 cites W3097804851 @default.
- W4313291217 cites W3114137134 @default.
- W4313291217 cites W3117495151 @default.
- W4313291217 cites W3117528838 @default.
- W4313291217 cites W3124495982 @default.
- W4313291217 cites W3137665052 @default.
- W4313291217 cites W3138622452 @default.
- W4313291217 cites W3154404459 @default.
- W4313291217 cites W3184980526 @default.
- W4313291217 cites W3208560513 @default.
- W4313291217 cites W323404752 @default.
- W4313291217 cites W4205713982 @default.
- W4313291217 cites W4206692153 @default.
- W4313291217 cites W4213279801 @default.
- W4313291217 cites W4223432987 @default.
- W4313291217 cites W4225897724 @default.
- W4313291217 cites W4226076932 @default.
- W4313291217 cites W4226133142 @default.
- W4313291217 cites W4252684946 @default.
- W4313291217 cites W4281752026 @default.
- W4313291217 cites W4281998067 @default.
- W4313291217 cites W4285034811 @default.
- W4313291217 cites W4285201879 @default.
- W4313291217 cites W4289236186 @default.
- W4313291217 cites W4292336562 @default.
- W4313291217 doi "https://doi.org/10.1109/tbdata.2022.3232761" @default.
- W4313291217 hasPublicationYear "2023" @default.
- W4313291217 type Work @default.
- W4313291217 citedByCount "2" @default.
- W4313291217 countsByYear W43132912172023 @default.
- W4313291217 crossrefType "journal-article" @default.
- W4313291217 hasAuthorship W4313291217A5014921188 @default.
- W4313291217 hasAuthorship W4313291217A5029072443 @default.
- W4313291217 hasAuthorship W4313291217A5029344996 @default.
- W4313291217 hasAuthorship W4313291217A5033098099 @default.
- W4313291217 hasAuthorship W4313291217A5056949686 @default.
- W4313291217 hasAuthorship W4313291217A5063205295 @default.
- W4313291217 hasAuthorship W4313291217A5076869167 @default.
- W4313291217 hasAuthorship W4313291217A5084148795 @default.
- W4313291217 hasBestOaLocation W43132912171 @default.
- W4313291217 hasConcept C109718341 @default.
- W4313291217 hasConcept C119857082 @default.
- W4313291217 hasConcept C121332964 @default.
- W4313291217 hasConcept C124101348 @default.
- W4313291217 hasConcept C138885662 @default.
- W4313291217 hasConcept C148483581 @default.
- W4313291217 hasConcept C153180895 @default.
- W4313291217 hasConcept C154945302 @default.
- W4313291217 hasConcept C181335050 @default.
- W4313291217 hasConcept C2776401178 @default.
- W4313291217 hasConcept C2778755073 @default.
- W4313291217 hasConcept C41008148 @default.