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Feature Selection for High Dimensional Classification using A Competitive Swarm Optimizer

Jin, Y, Gu, S and Cheng, R (2016) Feature Selection for High Dimensional Classification using A Competitive Swarm Optimizer Soft Computing.

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Abstract

When solving many machine learning problems such as classification, there exists a large number of input features. However, not all features are relevant for solving the problem, and sometimes, including irrelevant features may deteriorate the learning performance.Please check the edit made in the article title Therefore, it is essential to select the most relevant features, which is known as feature selection. Many feature selection algorithms have been developed, including evolutionary algorithms or particle swarm optimization (PSO) algorithms, to find a subset of the most important features for accomplishing a particular machine learning task. However, the traditional PSO does not perform well for large-scale optimization problems, which degrades the effectiveness of PSO for feature selection when the number of features dramatically increases. In this paper, we propose to use a very recent PSO variant, known as competitive swarm optimizer (CSO) that was dedicated to large-scale optimization, for solving high-dimensional feature selection problems. In addition, the CSO, which was originally developed for continuous optimization, is adapted to perform feature selection that can be considered as a combinatorial optimization problem. An archive technique is also introduced to reduce computational cost. Experiments on six benchmark datasets demonstrate that compared to the canonical PSO-based and a state-of-the-art PSO variant for feature selection, the proposed CSO-based feature selection algorithm not only selects a much smaller number of features, but result in better classification performance as well.

Item Type: Article
Subjects : Computing
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
NameEmailORCID
Jin, YUNSPECIFIEDUNSPECIFIED
Gu, SUNSPECIFIEDUNSPECIFIED
Cheng, RUNSPECIFIEDUNSPECIFIED
Date : 7 October 2016
Identification Number : 10.1007/s00500-016-2385-6
Copyright Disclaimer : The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-016-2385-6
Uncontrolled Keywords : Feature selection, High dimensionality, Large-scale optimization, Classification, Competitive swarm optimization
Depositing User : Symplectic Elements
Date Deposited : 17 Oct 2016 10:02
Last Modified : 07 Oct 2017 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/812470

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