wolffd@0: function net = knn(nin, nout, k, tr_in, tr_targets)
wolffd@0: %KNN	Creates a K-nearest-neighbour classifier.
wolffd@0: %
wolffd@0: %	Description
wolffd@0: %	NET = KNN(NIN, NOUT, K, TR_IN, TR_TARGETS) creates a KNN model NET
wolffd@0: %	with input dimension NIN, output dimension NOUT and K neighbours.
wolffd@0: %	The training data is also stored in the data structure and the
wolffd@0: %	targets are assumed to be using a 1-of-N coding.
wolffd@0: %
wolffd@0: %	The fields in NET are
wolffd@0: %	  type = 'knn'
wolffd@0: %	  nin = number of inputs
wolffd@0: %	  nout = number of outputs
wolffd@0: %	  tr_in = training input data
wolffd@0: %	  tr_targets = training target data
wolffd@0: %
wolffd@0: %	See also
wolffd@0: %	KMEANS, KNNFWD
wolffd@0: %
wolffd@0: 
wolffd@0: %	Copyright (c) Ian T Nabney (1996-2001)
wolffd@0: 
wolffd@0: 
wolffd@0: net.type = 'knn';
wolffd@0: net.nin = nin;
wolffd@0: net.nout = nout;
wolffd@0: net.k = k;
wolffd@0: errstring = consist(net, 'knn', tr_in, tr_targets);
wolffd@0: if ~isempty(errstring)
wolffd@0:   error(errstring);
wolffd@0: end
wolffd@0: net.tr_in = tr_in; 
wolffd@0: net.tr_targets = tr_targets;
wolffd@0: