Feeding the data to classifier

    I am working on transformer fault diagnosis

    I have a matrix of size 25x6

    Testing samples of SVM = [13 thermal heating samples; 2 highenergy 
    discharge samples; 4 normal state; 6 low-energy discharge samples ]

C=

35  25  0  23  22
160  90  27  17  5
565  93  34  47  0
150  53  34  20  0
980  73  58  12  0
176  206  47.7  75.7  68.7
293  50  13  115  120
443  85  9.5  103  174
73  520  140  1200  6
42  97  157  600  0
766  993  116  665  4
16  237  92  470  0
15  125  29  574  7
120  120  33  84  0.55
5  217  69  523  6
0  434  226  387  0
2844  8517  4422  10196  39
117  357  92  468  4
80  153  42  276  18
86  110  18  92  7.4
8  631  254  2020  39
10  4  3  33  6
14.7  3.8  10.5  2.7  0.2
6.7  10  11  71  3.9
0.33  0.26  0.04  0.27  0

    I have to classify the above dataste using SVM as described below

    With the below  output, we can distinguish the 4 normal
    samples from the other 21 samples of the other three fault
    types.

    Output of SVM is as follows:
    Columns 1 through 15
    1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

    Columns 16 through 25
    −1 −1 −1 −1 1 1 1 1 1 1

    please help how to process