Abstract
In this paper we propose integrating two collective computational intelligence techniques: gene expression programming and cellular evolutionary algorithms with a view to induce expression trees, which, subsequently, serve as weak classifiers. From these classifiers stronger ensemble classifiers are constructed using majority-voting and boosting techniques. The paper includes the discussion of the validating experiment result confirming high quality of the proposed ensemble classifiers.
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Jędrzejowicz, J., Jędrzejowicz, P. (2011). Cellular Gene Expression Programming Classifier Learning. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence V. Lecture Notes in Computer Science, vol 6910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24016-4_4
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DOI: https://doi.org/10.1007/978-3-642-24016-4_4
Publisher Name: Springer, Berlin, Heidelberg
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