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From: Q on 1 Jul 2010 14:52
Hi,
this is my first post here
I hope someone could answer my question

I am trying to test the svmclassify code from the help
% Load the data and select features for classification
load variables.mat
data = [Matrix(:,3), Matrix(:,4),Matrix(:,5),Matrix(:,6),Matrix(:,7),Matrix(:,8),Matrix(:,9),Matrix(:,10),Matrix(:,11),Matrix(:,12)];
% Extract the Setosa class
groups = ismember(species,'member');
% Randomly select training and test sets
[train, test] = crossvalind('holdOut',groups);
cp = classperf(groups);
% Use a linear support vector machine classifier
svmStruct = svmtrain(data(train,:),groups(train),'showplot',true);
classes = svmclassify(svmStruct,data(test,:),'showplot',true);
% See how well the classifier performed
classperf(cp,classes,test);
cp.CorrectRate

the problem is that my matrix is not 2D matrix
is this consider a multi-classes SVM?? and I can't use this code??

thanks in advanced
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