A least mean-squared error approach to syntactic classification
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1Department of Mathematics, Arizona State University, Tempe, AZ 85281.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
Abstract:
The usual approach to numerical training in syntactic pattern recognition involves estimation of the production probabilities of stochastic context-free grammars. Here we describe a different approach, namely that of finding an LMSE discriminant hyperplane between sets of class samples in a space of ``structural indices'' determined by a context-free grammar.
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