KNNCLASS |
k-Nearest Neighbours classifier.
Synopsis:
y = knnclass(X,model)
Description:
The input feature vectors X are classified using the K-NN
rule defined by the input model.
Input:
X [dim x num_data] Data to be classified.
model [struct] Model of K-NN classfier:
.X [dim x num_prototypes] Prototypes.
.y [1 x num_prototypes] Labels of prototypes.
.K [1x1] Number of used nearest-neighbours.
Output:
y [1 x num_data] Classified labels of testing data.
Example:
trn = load('riply_trn');
tst = load('riply_tst');
ypred = knnclass(tst.X,knnrule(trn,5));
cerror( ypred, tst.y )
See also
KNNRULE.
(c) Statistical Pattern Recognition Toolbox, (C) 1999-2003,
Written by Vojtech Franc and Vaclav Hlavac,
Czech Technical University Prague,
Faculty of Electrical engineering,
Center for Machine Perception
Modifications:
19-may-2003, VF
18-sep-2002, V.Franc