Sha256: 2d3c845833f9343312314eca7f597a03537d643baa5dd95241377e4fecec9bac
Contents?: true
Size: 1.95 KB
Versions: 14
Compression:
Stored size: 1.95 KB
Contents
/************************************************************************/
/* */
/* kernel.h */
/* */
/* User defined kernel function. Feel free to plug in your own. */
/* */
/* Copyright: Thorsten Joachims */
/* Date: 16.12.97 */
/* */
/************************************************************************/
/* KERNEL_PARM is defined in svm_common.h The field 'custom' is reserved for */
/* parameters of the user defined kernel. You can also access and use */
/* the parameters of the other kernels. Just replace the line
return((double)(1.0));
with your own kernel. */
/* Example: The following computes the polynomial kernel. sprod_ss
computes the inner product between two sparse vectors.
return((CFLOAT)pow(kernel_parm->coef_lin*sprod_ss(a->words,b->words)
+kernel_parm->coef_const,(double)kernel_parm->poly_degree));
*/
/* If you are implementing a kernel that is not based on a
feature/value representation, you might want to make use of the
field "userdefined" in SVECTOR. By default, this field will contain
whatever string you put behind a # sign in the example file. So, if
a line in your training file looks like
-1 1:3 5:6 #abcdefg
then the SVECTOR field "words" will contain the vector 1:3 5:6, and
"userdefined" will contain the string "abcdefg". */
double custom_kernel(KERNEL_PARM *kernel_parm, SVECTOR *a, SVECTOR *b)
/* plug in you favorite kernel */
{
return((double)(1.0));
}
Version data entries
14 entries across 14 versions & 2 rubygems