Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61475
Title: An alternative way of presenting statistical test results when evaluating the performance of stochastic approaches
Contributor(s): Weise, Thomas (author); Chiong, Raymond  (author)orcid 
Publication Date: 2015-01-05
DOI: 10.1016/j.neucom.2014.06.071
Handle Link: https://hdl.handle.net/1959.11/61475
Abstract: 

Stochastic approaches such as evolutionary algorithms have been widely used in various science and engineering problems. When comparing the performance of a set of stochastic algorithms, it is necessary to statistically evaluate which algorithms are the most suitable for solving a given problem. The outcome of statistical tests comparing N ≥ 2 processes, where N is the number of algorithms, is often presented in tables. This can become confusing for larger numbers of N. Such a scenario is, however, very common in both numerical and combinatorial optimization as well as in the domain of stochastic algorithms in general. In this letter, we introduce an alternative way of visually presenting the results of statistical tests for multiple processes in a compact and easy-to-read manner using a directed acyclic graph (DAG), in the form of a simplified Hasse diagram. The rationale of doing so is based on the fact that the outcome of the tests is always at least a strict partial order, which can be appropriately presented via a DAG. The goal of this brief communication is to promote the use of this approach as a means for presenting the results of comparisons between different optimization methods.

Publication Type: Journal Article
Source of Publication: Neurocomputing, 147(1), p. 235-238
Publisher: Elsevier BV
Place of Publication: The Netherlands
ISSN: 1872-8286
0925-2312
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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