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Arabian Journal for Science and Engineering
Published in: Arabian Journal for Science and Engineering 11/2019

11-07-2019 | Research Article - Computer Engineering and Computer Science

A Novel Distance Metric Based on Differential Evolution

Author: Ömer Faruk Ertuğrul

Published in: Arabian Journal for Science and Engineering | Issue 11/2019

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Abstract

Distance has been employed as a representation of similarity for half a century. Many different distance metrics have been proposed in this duration such as Euclidean, Manhattan, Minkowski and weighted Euclidean distance metrics. Each of them has its own characteristics and is calculated in different formulations/manners. In this paper, a novel distance metric, which has a high adaptation capability, was proposed. In order to increase the adaptation ability of the proposed distance metric, its parameters were optimized according to the employed dataset by differential evolution (DE), which is a metaheuristic optimization method. The proposed distance metric was employed in the k-nearest neighbor, and 30 different benchmark datasets were used in the evaluation of the proposed approach. Each of the parameters of the novel distance metric and the parameters of DE was assessed based on the obtained accuracies. Obtained results validated the applicability of the proposed distance metric and the proposed approach.
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Metadata
Title
A Novel Distance Metric Based on Differential Evolution
Author
Ömer Faruk Ertuğrul
Publication date
11-07-2019
Publisher
Springer Berlin Heidelberg
Published in
Arabian Journal for Science and Engineering / Issue 11/2019
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-019-04003-5

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