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1 /************************************************************************/
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2 /* */
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3 /* kernel.h */
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4 /* */
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5 /* User defined kernel function. Feel free to plug in your own. */
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6 /* */
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7 /* Copyright: Thorsten Joachims */
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8 /* Date: 16.12.97 */
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9 /* */
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10 /************************************************************************/
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11
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12 /* KERNEL_PARM is defined in svm_common.h The field 'custom' is reserved for */
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13 /* parameters of the user defined kernel. You can also access and use */
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14 /* the parameters of the other kernels. Just replace the line
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15 return((double)(1.0));
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16 with your own kernel. */
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17
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18 /* Example: The following computes the polynomial kernel. sprod_ss
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19 computes the inner product between two sparse vectors.
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20
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21 return((CFLOAT)pow(kernel_parm->coef_lin*sprod_ss(a->words,b->words)
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22 +kernel_parm->coef_const,(double)kernel_parm->poly_degree));
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23 */
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24
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25 /* If you are implementing a kernel that is not based on a
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26 feature/value representation, you might want to make use of the
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27 field "userdefined" in SVECTOR. By default, this field will contain
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28 whatever string you put behind a # sign in the example file. So, if
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29 a line in your training file looks like
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30
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31 -1 1:3 5:6 #abcdefg
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32
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33 then the SVECTOR field "words" will contain the vector 1:3 5:6, and
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34 "userdefined" will contain the string "abcdefg". */
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35
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36 double custom_kernel(KERNEL_PARM *kernel_parm, SVECTOR *a, SVECTOR *b)
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37 /* plug in you favorite kernel */
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38 {
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39 return((double)(1.0));
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40 }
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