Improved binary particle swarm optimization for feature selection with new initialization and search space reduction strategies
Feature selection (FS) is an important preprocessing technique for dimensionality reduction in classification problems. Particle swarm optimization (PSO) algorithms have been widely used as the optimizers for FS problems. However, with the increase of data dimensionality, the search space expands dr...
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Published in | Applied soft computing Vol. 106; p. 107302 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.07.2021
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Subjects | |
Online Access | Get full text |
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