Competitive Particle Swarm Optimization for Multi-Category Text Feature Selection

Competitive Particle Swarm Optimization for Multi-Category Text Feature Selection

Multi-label feature selection is an important task for text categorization. This is because it enables learning algorithms to focus on essential features that foreshadow relevant categories, thereby improving the accuracy of text categorization. Recent studies have considered the hybridization of ev...

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Bibliographic Details
Main Authors: Jaesung Lee, Jaegyun Park, Hae-Cheon Kim, Dae-Won Kim
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Entropy
Subjects:
multi-label text categorization
feature selection
hybrid search
evolutionary algorithm
particle swarm optimization
Online Access:https://www.mdpi.com/1099-4300/21/6/602

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https://www.mdpi.com/1099-4300/21/6/602

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