Influence of data description on efficiency of learning and job artificial neural network on example of identification of proteins

Authors

  • Jacek BARTMAN Uniwersytet Rzeszowski, Instytut Techniki, Polska

Keywords:

artificial neural network, learning

Abstract

Learning feedforward multilayer neural networks is an issue widely discussed in the literature. The authors of the most works focus on methods of learning, much less work is devoted to the influence of data preprocessing on learning and the efficiency of the network. If learning of artificial neural networks is finding the mapping function set of input data into a set of expected responses, what you can expect if you change the description of the data learners? Changes of mapping functions, and so we are looking for another function, so it is possible that the encoding of data affects the efficiency of learning and job of the network. This paper touches the issue presented by examining the impact of coding method information about the proteins on the effectiveness of learning and the work of the neural network identifies the type of protein.

Published

2013-12-15

How to Cite

BARTMAN, J. (2013). Influence of data description on efficiency of learning and job artificial neural network on example of identification of proteins. Journal of Education, Technology and Computer Science, 8(2), 358–365. Retrieved from https://journals.ur.edu.pl/jetacomps/article/view/6785

Issue

Section

PROBLEMS OF MATHEMATICAL AND COMPUTER MODELING

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