The new method of the selection of features for the k-NN classifier in the arteriovenous fistula state estimation
Marcin Grochowina, Lucyna Leniowska
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 281–285 (2016)
Abstract. In this paper the application of a new method of features selection was presented. Its effects were compared with several other methods of features selection. The study were performed using a data set containing samples of the sound signal emitted by the arteriovenous fistula. The aim was to create a solution with multiclass classification based on the k-NN classifier family allowing for effective and credible assessment of the state of arterial-venous fistula.
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