Incremetal GEP-based ensemble classifier
Joanna Jędrzejowicz , Piotr Jędrzejowicz
AbstractIn 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.
|Publication size in sheets||0.5|
|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 English||incremental classification, gene expression programming, metagene|
|Score|| = 15.0, BookChapterSeriesAndMatConfByIndicator|
= 15.0, BookChapterSeriesAndMatConfByIndicator
|Publication indicators||= 2; : 2016 = 0.367|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.