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Use of Neural Networks for Empirical Data
Asked by Domenico Tatone (teacher), Mayfield Secondary School on Friday
May 3, 1996:
I am currently working on a thesis on group dynamics. In my
attempt to quantify qualitative research (i.e. interpret responses to
interview questions), I am resorting to the development of neural
networks. My question relates to the utility of neural networks in
empirical studies. Could you direct me to resources that would enable
me to implement the proper formation of neural networks, and their
respective instruments for testing hypotheses (i.e equations) that
emerge from such models. Furthermore, how can fuzzy logic be utilized
in conjunction to neural networks.
Here is a reply to your question from a researcher in the
Neural Network Research Group
here at the University of Toronto:
It is a little unclear to me what the question is about. But I can
certainly recommend an introduction to neural networks. Hertz, Krogh
and Palmers "Introduction to the theory of neural computation" is in
my opinion by far the best introduction, although I guess a little
dated by now. It requires a certain level of mathematical
sophistication. Of more recent books there is (physicist) Chris
Bishop "Statistical learning in neural networks" and a book by
(statistician) Brian Ripley with roughly the same title. Let me know
if you have trouble locating any of these and I'll send you proper
references.
These general references may not answer your question, but feel free
to come back here with more specific questions if you have them.
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