Gene expression programming as a data classification tool. A review

Joanna Jędrzejowicz , Piotr Jędrzejowicz

Abstract

The paper reviews classification algorithms based on Gene Expression Programming (GEP) used for mining the real-life datasets. Our aim is to show, chronologically, most important developments as well as the current state-of-the-art in the area of GEP-based classifiers, with a view to attract further real life applications. We begin with reviewing approaches to building basic, stand alone, GEP classifiers and eventually, combining them into the classifier ensemble. In the following part of the paper we describe and illustrate with example several hybrid solutions where GEP is integrated with other methods. Next, we review specialized and dedicated methods including multiple criteria and incremental GEP-based classification tools. Final part of the paper reviews specialized GEP-based classifiers used to mine the real-life datasets.
Author Joanna Jędrzejowicz (FMPI / II)
Joanna Jędrzejowicz,,
- Institute of Informatics
, Piotr Jędrzejowicz
Piotr Jędrzejowicz,,
-
Journal seriesJournal of Intelligent & Fuzzy Systems, ISSN 1064-1246 [1875-8967], (A 25 pkt)
Issue year2019
Vol36
No1
Pages91-100
Publication size in sheets0.5
Keywords in Englishgene expression programming, classification, classifier ensemble
ASJC Classification1702 Artificial Intelligence; 2200 General Engineering; 2613 Statistics and Probability
DOIDOI:10.3233/JIFS-18026
Languageen angielski
Score (nominal)25
ScoreMinisterial score = 20.0, 15-04-2019, ArticleFromJournal
Ministerial score (2013-2016) = 25.0, 15-04-2019, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 0.814; WoS Impact Factor: 2017 = 1.426 (2) - 2017=1.594 (5)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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