bsvm_util.c

留一模型选择法leave-one-out model selection

#include <sys/times.h>
#include <time.h>
#include <math.h>
#include "bsvm.h"
#include "bsvm_util.h"
extern kernel_param_t kernel_param;

double sparsedot(feature_t *vec1, feature_t *vec2)
{
	/* vec1 dot vec2 */
	double ans = 0;
	feature_t *p1 = vec1, *p2 = vec2;

	while (p1->num != -1 && p2->num !=-1)
	{
		if(p1->num == p2->num)
		{
			ans += p1->value*p2->value;
			p1++;
			p2++;
		}
		else
		{
			if(p1->num > p2->num)
				p2++;
			else
				p1++;
		}
	}
	return ans;
}

double kernel_rbf(sample_t* s1, sample_t* s2)
{
	/* |x - y|^2 = |x|^2 + |y|^2 - 2*(x dot y) */
	return exp(-kernel_param.gamma*(s1->twonorm_sq +
	s2->twonorm_sq - 2*sparsedot(s1->v, s2->v))) + 1;	
}

double kernel_poly(sample_t* s1, sample_t* s2)
{
	return pow(kernel_param.gamma*sparsedot(s1->v, s2->v) +
	kernel_param.coef0, kernel_param.degree) + 1;
}

double kernel_linear(sample_t *s1, sample_t *s2)
{
	return sparsedot(s1->v, s2->v) + 1;
}

double kernel_tanh(sample_t* s1, sample_t* s2)
{
	return tanh(kernel_param.gamma*sparsedot(s1->v, s2->v) +
	kernel_param.coef0) + 1;
}

/* return number of samples in dataset */
int get_N(FILE *dataset)
{
	char line[MAXLEN];
	int i = 0;
	while (fgets(line, MAXLEN, dataset) != NULL)
		i++;
	if (i == 0)
		myerror("Data set is empty");
	rewind(dataset);
	return i;
}

void get_nnz(FILE *dataset, int *nnzl)
{
	char line[MAXLEN];
	int i, nnz, j;

	for(i=0;fgets(line, MAXLEN, dataset) != NULL;i++)
	{
		/* number of nonzero element in this sparse vector */
		for(nnz=0,j=0;line[j];j++)
			if (line[j] == ':')
				nnz++;
		nnzl[i] = nnz;
	}
	rewind(dataset);
}

double get_utime()
{
        struct tms buffer;
        times(&buffer);
        return ((double) ((int) buffer.tms_utime)/CLK_TCK);
}

void myerror(char *errormsg)
{
	fprintf(stderr, "%s.\n", errormsg);
	exit(1);
}

void *xmalloc(size_t size)
{
	void *ptr = (void *) malloc(size);
	if (!ptr)
		myerror("Out of memory");
	return ptr;
}