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Design of Higher Order Quadrature Mirror Filter Bank Using Simulated Annealing-Based Multi-swarm Cooperative Particle Swarm Optimization Read chapter Read first chapter

2019 | OriginalPaper | Chapter

S-shaped Binary Whale Optimization Algorithm for Feature Selection

Authors : Abdelazim G. Hussien, Aboul Ella Hassanien, Essam H. Houssein, Siddhartha Bhattacharyya, Mohamed Amin

Published in: Recent Trends in Signal and Image Processing

Publisher: Springer Singapore

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Abstract

Whale optimization algorithm is one of the recent nature-inspired optimization technique based on the behavior of bubble-net hunting strategy. In this paper, a novel binary version of whale optimization algorithm (bWOA) is proposed to select the optimal feature subset for dimensionality reduction and classifications problem. The new approach is based on a sigmoid transfer function (S-shape). By dealing with the feature selection problem, a free position of the whale must be transformed to their corresponding binary solutions. This transformation is performed by applying an S-shaped transfer function in every dimension that defines the probability of transforming the position vectors’ elements from 0 to 1 and vice versa and hence force the search agents to move in a binary space. K-NN classifier is applied to ensure that the selected features are the relevant ones. A set of criteria are used to evaluate and compare the proposed bWOA-S with the native one over eleven different datasets. The results proved that the new algorithm has a significant performance in finding the optimal feature.

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Metadata
Title
S-shaped Binary Whale Optimization Algorithm for Feature Selection
Authors
Abdelazim G. Hussien
Aboul Ella Hassanien
Essam H. Houssein
Siddhartha Bhattacharyya
Mohamed Amin
Copyright Year
2019
Publisher
Springer Singapore
Book
Recent Trends in Signal and Image Processing

Print ISBN: 978-981-10-8862-9

Electronic ISBN: 978-981-10-8863-6

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-10-8863-6_9