/* call as model = mexsvmlearn(data,labels,options) */
void mexFunction(int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
{
int rows, cols,i,j,offset;
double *kern,k;
DOC **docsA, **docsB;
SVECTOR *a, *b;
MODEL *model;
global_init( );
/* load model parameters from the "model" parameter */
model = restore_model((mxArray *)prhs[2]);
rows = mxGetM(prhs[0]);
cols = mxGetN(prhs[0]);
/* load the testing arrays into docs */
mexToDOC((mxArray *)prhs[0], NULL, &docsA, NULL, NULL, NULL);
mexToDOC((mxArray *)prhs[1], NULL, &docsB, NULL, NULL, NULL);
/* setup output environment */
plhs[0] = mxCreateDoubleMatrix(1,1,mxREAL);
kern = mxGetPr(plhs[0]);
a = docsA[0]->fvec;
b = docsB[0]->fvec;
kern[0] = single_kernel(&(model->kernel_parm), a, b);
global_destroy();
}
double kernel(KERNEL_PARM *kernel_parm, DOC *a, DOC *b)
/* calculate the kernel function */
{
double sum=0;
SVECTOR *fa,*fb;
if(kernel_parm->kernel_type == GRAM) { /* use value from explicitly */
if((a->kernelid>=0) && (b->kernelid>=0)) /* stored gram matrix */
return(kernel_parm->gram_matrix->element[MAX(a->kernelid,b->kernelid)]
[MIN(a->kernelid,b->kernelid)]);
else
return(0); /* in case it is called for unknown vector */
}
/* in case the constraints are sums of feature vector as represented
as a list of SVECTOR's with their coefficient factor in the sum,
take the kernel between all pairs */
for(fa=a->fvec;fa;fa=fa->next) {
for(fb=b->fvec;fb;fb=fb->next) {
if(fa->kernel_id == fb->kernel_id)
sum+=fa->factor*fb->factor*single_kernel(kernel_parm,fa,fb);
}
}
return(sum);
}
double kernel(KERNEL_PARM *kernel_parm, DOC *a, DOC *b)
/* calculate the kernel function */
{
double sum=0;
SVECTOR *fa,*fb;
/* in case the constraints are sums of feature vector as represented
as a list of SVECTOR's with their coefficient factor in the sum,
take the kernel between all pairs */
for(fa=a->fvec;fa;fa=fa->next) {
for(fb=b->fvec;fb;fb=fb->next) {
if(fa->kernel_id == fb->kernel_id)
sum+=fa->factor*fb->factor*single_kernel(kernel_parm,fa,fb);
}
}
return(sum);
}
/* call as model = mexsvmlearn(data,labels,options) */
void mexFunction(int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
{
int rows, cols,i,j,offset;
double *kern,k;
DOC **docs;
SVECTOR *a, *b;
MODEL *model;
global_init();
/* load model parameters from the "model" parameter */
model = restore_model((mxArray *)prhs[1]);
rows = mxGetM(prhs[0]);
cols = mxGetN(prhs[0]);
/* load the testing arrays into docs */
mexToDOC((mxArray *)prhs[0], NULL, &docs, NULL, NULL, NULL);
/* setup output environment */
plhs[0] = mxCreateDoubleMatrix(rows,rows,mxREAL);
kern = mxGetPr(plhs[0]);
for (i = 0; i < rows; i++) {
a = docs[i]->fvec;
for (j = 0; j < rows; j++) {
b = docs[j]->fvec;
k = single_kernel(&(model->kernel_parm), a, b);
offset = computeOffset(rows, rows, i, j);
kern[offset] = k;
}
}
global_destroy();
}
