/netlab/knn.m
http://princeton-mvpa-toolbox.googlecode.com/ · MATLAB · 35 lines · 11 code · 5 blank · 19 comment · 1 complexity · beede5e80f0a8295dca33b3666b052d6 MD5 · raw file
- function net = knn(nin, nout, k, tr_in, tr_targets)
- %KNN Creates a K-nearest-neighbour classifier.
- %
- % Description
- % NET = KNN(NIN, NOUT, K, TR_IN, TR_TARGETS) creates a KNN model NET
- % with input dimension NIN, output dimension NOUT and K neighbours.
- % The training data is also stored in the data structure and the
- % targets are assumed to be using a 1-of-N coding.
- %
- % The fields in NET are
- % type = 'knn'
- % nin = number of inputs
- % nout = number of outputs
- % tr_in = training input data
- % tr_targets = training target data
- %
- % See also
- % KMEANS, KNNFWD
- %
- % Copyright (c) Ian T Nabney (1996-2001)
- net.type = 'knn';
- net.nin = nin;
- net.nout = nout;
- net.k = k;
- errstring = consist(net, 'knn', tr_in, tr_targets);
- if ~isempty(errstring)
- error(errstring);
- end
- net.tr_in = tr_in;
- net.tr_targets = tr_targets;