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. © 2012 Springer-Verlag.
CITATION STYLE
Kordos, M., & Blachnik, M. (2012). Instance selection with neural networks for regression problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7553 LNCS, pp. 263–270). https://doi.org/10.1007/978-3-642-33266-1_33
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