Titlebook: Artificial Intelligence and Soft Computing; 13th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

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Pädiatrische und geriatrische HNO-Heilkundee RF proximity matrix has better classification accuracy in comparison to SOM learned with Euclidean distance. Presented approach enables better understanding of the RF and additionally improves accuracy of the SOM.

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0302-9743 nce and Soft Computing, ICAISC 2014, held in Zakopane, Poland in June 2014. The 139 revised full papers presented in the volumes, were carefully reviewed and selected from 331 submissions. The 69 papers included in the first volume are focused on the following topical sections: Neural Networks and T

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Pädiatrische und geriatrische HNO-Heilkundeeveloped by us Generalized CNN and Generalized ENN algorithms. Results of the comparative experimental study performed using different configurations on several datasets shows that the approachbased on bagging allowed for significant improvement, especially in terms of data compression.

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Äußerer Hals und Halsweichteilen this paper we are focusing on applying data compression in the classification of EEG signals. We combine a vector quantization and the normalized compression distance for proper classification of a finger movement data.

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https://doi.org/10.1007/978-3-662-62536-1ecision of medical diagnostic systems. We show that also the structure is not that important – diagnostic accuracy of several medical diagnostic models changes minimally when we subject their structures to such transformations as arc removal and arc reversal.

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