How to train using SVM?

Hello,

I am attaching a code below for training using SVM for Faces.

I am proceeding in the following way:-

In training matrix i have taken 2 rows each row has 4 samples of a individual. Now i have fixed the target matrix at:-

labelData(1:4,:) = 1;
labelData(5:8,:) = 2;

Now i am training the data as follows:-

svmModel = svmtrain(arr1', labelData, ...'Autoscale',true, 'Showplot',true, 'Method','QP', ...'BoxConstraint',2e-1, 'Kernel_Function','rbf', RBF_Sigma',1); classes = svmclassify(svmModel,finaltest,'showplot','true') cp = classperf(cp, classes, finaltest')

The final list of features given are:-

arr1 =

    0.1058   -0.5517   -1.3537   62.4660  119.9515  138.0683  137.9539  127.3512  120.5434   95.0995
 -252.4978   -6.1384   -6.5467   -1.4940   31.6996   89.8276  118.6320  120.7114   86.2801   42.4085
 -541.0102 -129.8960 -128.3588 -136.9744 -105.7236  -64.3677  -10.4804   30.5314   45.8545   22.7236
 -541.0102 -250.1544 -128.3588 -139.1115 -107.8966  -87.0327  -10.4804   30.5314   45.8545   22.7236
 -542.6045 -545.1539 -139.5034 -139.1115 -139.8038  -87.0327  -39.0280  -28.4102  -20.8262  -33.8483
 -542.6045 -545.1539 -154.1400 -145.5581 -139.8038  -98.5822  -75.3121  -35.7535  -20.8262  -33.8483
 -546.0365 -548.3869 -154.1400 -169.4303 -170.3015 -123.2716  -75.3121  -35.7535  -37.6052  -63.0706
 -546.3883 -548.3869 -208.0748 -169.4303 -170.3015 -123.2716 -110.6051 -137.7718 -163.2197 -203.0798

My question is how to obtain the classification plot of SVM for plotting these vectors as I am not getting any plot? Any help would be highly appreciated.

[Walter Roberson]

duplicate is http://www.mathworks.co.uk/matlabcentral/answers/55685-query-regarding-classification-of-faces-using-svm