Instance selection with neural networks for regression problems

Authors:
Mirosław Kordos;Marcin Blachnik
Affiliations:
Department of Mathematics and Computer Science, University of Bielsko-Biala, Bielsko-Biała, Poland;Department of Management and Informatics, Silesian University of Technology, Katowice, Poland
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Year:
2012

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Abstract

The paper presents algorithms for instance selection for regression problems based upon the CNN and ENN solutions known for classification tasks. A comparative experimental study is performed on several datasets using multilayer perceptrons and k-NN algorithms with different parameters and their various combinations as the method the selection is based on. Also various similarity thresholds are tested. The obtained results are evaluated taking into account the size of the resulting data set and the regression accuracy obtained with multilayer perceptron as the predictive model and the final recommendation regarding instance selection for regression tasks is presented.