The reduced Parzen classifier
Keinosuke Fukunaga, R.R. Hayes · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1989
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.>