Pareto front feature selection based on artificial bee colony optimization

Author:

Hancer Emrah,Xue Bing,Zhang Mengjie,Karaboga Dervis,Akay Bahriye

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference48 articles.

1. Simulated binary crossover for continuous search space;Agrawal;Complex syst.,1995

2. Synchronous and asynchronous Pareto-based multi-objective artificial bee colony algorithms;Akay;J. Global Optim.,2013

3. Theory of the hypervolume indicator: optimal μ-distributions and the choice of the reference point;Auger,2009

4. M. Lichman, UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science, 2013. http://archive.ics.uci.edu/ml.

5. Using mutual information for selecting features in supervised neural net learning;Battiti;IEEE Trans. Neural Netw.,1994

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