Description of slclassify_eucnn

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slclassify_eucnn

PURPOSE

SLCLASSIFY_EUCNN Classifies samples using Euclidena-based NN

SYNOPSIS

function labels = slclassify_eucnn(centers, samples)

DESCRIPTION

SLCLASSIFY_EUCNN Classifies samples using Euclidena-based NN

 $ Syntax $
   - labels = slclassify_eucnn(centers, samples)

 $ Arguments $
   - centers:          the class centers
   - samples:          the samples to be classified
   - labels:           the classified result

 $ Description $
   - labels = slclassify_eucnn(centers, samples) classifies the samples to
     nearest centers based on Euclidean distances. The output labels
     indicate which nearest center the samples are classified to.

 $ History $
   - Created by Dahua Lin, on Aug 21, 2006

CROSS-REFERENCE INFORMATION

This function calls:

• slmetric_pw SLMETRIC_PW Compute the metric between column vectors pairwisely
• slclassify SLCLASSIFY Classifies a set of samples according to final scores

This function is called by:

• slgmm SLGMM Learns Gaussian Mixture model from samples

SOURCE CODE

0001 function labels = slclassify_eucnn(centers, samples)
0002 %SLCLASSIFY_EUCNN Classifies samples using Euclidena-based NN
0003 %
0004 % $ Syntax $
0005 %   - labels = slclassify_eucnn(centers, samples)
0006 %
0007 % $ Arguments $
0008 %   - centers:          the class centers
0009 %   - samples:          the samples to be classified
0010 %   - labels:           the classified result
0011 %
0012 % $ Description $
0013 %   - labels = slclassify_eucnn(centers, samples) classifies the samples to
0014 %     nearest centers based on Euclidean distances. The output labels
0015 %     indicate which nearest center the samples are classified to.
0016 %
0017 % $ History $
0018 %   - Created by Dahua Lin, on Aug 21, 2006
0019 %
0020 
0021 dists = slmetric_pw(centers, samples, 'eucdist');
0022 labels = slclassify(dists, 1:size(dists,1), 'low');

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