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PSO-Based Cooperative Learning Using Chunking

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Learning and Intelligent Optimization (LION 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12096))

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Abstract

Bio-inspired optimization consists of drawing inspiration from the behavior and internal functioning of physical, biological and social systems to design enhanced optimization algorithms. Our aim in this paper is to enhance the performance of particle swarm optimization (PSO), when optimizing the feature selection (FS) problem, by combining two bio-inspired approaches which are chunking and cooperative learning. The experimental results show that our hybrid wrapper-filter approach gives competitive results in terms of the predictive accuracy on the training set.

Supported by Alexander von Humboldt Foundation.

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Authors and Affiliations

  1. Institute of Information Systems, University of Hamburg, Hamburg, Germany

    Malek Sarhani & Stefan Voß

Authors
  1. Malek Sarhani
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  2. Stefan Voß
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Corresponding author

Correspondence to Malek Sarhani .

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Editors and Affiliations

  1. CARGO Lab., Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

  2. Center for Applied Optimization, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

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Sarhani, M., Voß, S. (2020). PSO-Based Cooperative Learning Using Chunking. In: Kotsireas, I., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2020. Lecture Notes in Computer Science(), vol 12096. Springer, Cham. https://doi.org/10.1007/978-3-030-53552-0_26

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