From Continuous Behaviour to Discrete Knowledge. Ledezma, A., Fernández, F., & Aler, R. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 2687, pages 217–224. 2003.
From Continuous Behaviour to Discrete Knowledge [link]Paper  doi  abstract   bibtex   
Neural networks have proven to be very powerful techniques for solving a wide range of tasks. However, the learned concepts are unreadable for humans. Some works try to obtain symbolic models from the networks, once these networks have been trained, allowing to understand the model by means of decision trees or rules that are closer to human understanding. The main problem of this approach is that neural networks output a continuous range of values, so even though a symbolic technique could be used to work with continuous classes, this output would still be hard to understand for humans. In this work, we present a system that is able to model a neural network behaviour by discretizing its outputs with a vector quantization approach, allowing to apply the symbolic method. © Springer-Verlag Berlin Heidelberg 2003.
@incollection{Ledezma2003a,
abstract = {Neural networks have proven to be very powerful techniques for solving a wide range of tasks. However, the learned concepts are unreadable for humans. Some works try to obtain symbolic models from the networks, once these networks have been trained, allowing to understand the model by means of decision trees or rules that are closer to human understanding. The main problem of this approach is that neural networks output a continuous range of values, so even though a symbolic technique could be used to work with continuous classes, this output would still be hard to understand for humans. In this work, we present a system that is able to model a neural network behaviour by discretizing its outputs with a vector quantization approach, allowing to apply the symbolic method. {\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},
author = {Ledezma, Agapito and Fern{\'{a}}ndez, Fernando and Aler, Ricardo},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/3-540-44869-1_28},
file = {:home/fernando/papers/tmp/10.1007{\%}2F3-540-44869-1{\_}28.pdf:pdf},
issn = {03029743},
pages = {217--224},
title = {{From Continuous Behaviour to Discrete Knowledge}},
url = {http://link.springer.com/10.1007/3-540-44869-1{\_}28},
volume = {2687},
year = {2003}
}

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