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The reduced Parzen classifier

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2 Author(s)
Fukunaga, K. ; Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA ; Hayes, R.R.

The Parzen density estimate is known to be an effective tool for estimating the Bayes error, given a set of training samples from the class distributions. An algorithm is developed to select a given number of representative samples whose Parzen density estimate closely matches that of the entire sample set. Using this reduced representative set, a piecewise quadratic classifier which provides nearly optimal performance is designed.<>

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:11 ,  Issue: 4 )