Incremetal GEP-based ensemble classifier

Joanna Jędrzejowicz , Piotr Jędrzejowicz


In this paper we propose a new incremental Gene Expression Programming (GEP) ensemble classifier. Our base classifiers are induced from a chunk of data instances using GEP. Size of the chunk controls the number of instances with known class labels used to induce base classifiers iteratively. Instances with unknown class label are classified in sequence, one by one. It is assumed that after a decision as to the class label of the new instance has been taken its true class label is revealed. From a set of base classifier a metagene is induced and used to predict class label of instances with unknown class labels. To validate the approach an extensive computational experiment has been carried-out.
Author Joanna Jędrzejowicz (FMPI/II)
Joanna Jędrzejowicz,,
- Institute of Informatics
, Piotr Jędrzejowicz
Piotr Jędrzejowicz,,
Publication size in sheets0.50
Book Czarnowski Ireneusz, Howlett Robert J. , Jain Lakhmi C. (eds.): Intelligent decision technologies 2017: proceedings of the 9th KES International Conference on Intelligent Decision Technologies (KES-IDT 2017), pt. 1, Smart Innovation, Systems and Technologies , no. 72, 2018, Springer, ISBN 978-3-319-59420-0, [978-3-319-59421-7], 347 p., DOI:10.1007/978-3-319-59421-7
Keywords in Englishincremental classification, gene expression programming, metagene
ASJC Classification1700 General Computer Science; 1800 General Decision Sciences
Languageen angielski
Score (nominal)20
Score sourcepublisherList
ScoreMinisterial score = 20.0, 21-05-2020, ChapterFromConference
Publication indicators WoS Citations = 2.000; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.337
Citation count*
Share Share

Get link to the record

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Are you sure?