#include?
#include?
#include?
#include?
#include?
#include?“svm.h“

int?print_null（const?char?*s...）?{return?0;}

static?int?（*info）（const?char?*fmt...）?=?&printf;

struct?svm_node?*x;
int?max_nr_attr?=?64;

struct?svm_model*?model;
int?predict_probability=0;

static?char?*line?=?NULL;
static?int?max_line_len;

static?char*?readline（FILE?*input）
{
	int?len;

	if（fgets（linemax_line_leninput）?==?NULL）
		return?NULL;

	while（strrchr（line‘\n‘）?==?NULL）
	{
		max_line_len?*=?2;
		line?=?（char?*）?realloc（linemax_line_len）;
		len?=?（int）?strlen（line）;
		if（fgets（line+lenmax_line_len-leninput）?==?NULL）
			break;
	}
	return?line;
}

void?exit_input_error（int?line_num）
{
	fprintf（stderr“Wrong?input?format?at?line?%d\n“?line_num）;
	exit（1）;
}

void?predict（FILE?*input?FILE?*output）
{
	int?correct?=?0;
	int?total?=?0;
	double?error?=?0;
	double?sump?=?0?sumt?=?0?sumpp?=?0?sumtt?=?0?sumpt?=?0;

	int?svm_type=svm_get_svm_type（model）;
	int?nr_class=svm_get_nr_class（model）;
	double?*prob_estimates=NULL;
	int?j;

	if（predict_probability）
	{
		if?（svm_type==NU_SVR?||?svm_type==EPSILON_SVR）
			info（“Prob.?model?for?test?data:?target?value?=?predicted?value?+?z\nz:?Laplace?distribution?e^（-|z|/sigma）/（2sigma）sigma=%g\n“svm_get_svr_probability（model））;
		else
		{
			int?*labels=（int?*）?malloc（nr_class*sizeof（int））;
			svm_get_labels（modellabels）;
			prob_estimates?=?（double?*）?malloc（nr_class*sizeof（double））;
			fprintf（output“labels“）;
			for（j=0;j				fprintf（output“?%d“labels[j]）;
			fprintf（output“\n“）;
			free（labels）;
		}
	}

	max_line_len?=?1024;
	line?=?（char?*）malloc（max_line_len*sizeof（char））;
	while（readline（input）?!=?NULL）
	{
		int?i?=?0;
		double?target_label?predict_label;
		char?*idx?*val?*label?*endptr;
		int?inst_max_index?=?-1;?//?strtol?gives?0?if?wrong?format?and?precomputed?kernel?has??start?from?0

		label?=?strtok（line“?\t\n“）;
		if（label?==?NULL）?//?empty?line
			exit_input_error（total+1）;

		target_label?=?strtod（label&endptr）;
		if（endptr?==?label?||?*endptr?!=?‘\0‘）
			exit_input_error（total+1）;

		while（1）
		{
			if（i>=max_nr_attr-1）	//?need?one?more?for?index?=?-1
			{
				max_nr_attr?*=?2;
				x?=?（struct?svm_node?*）?realloc（xmax_nr_attr*sizeof（struct?svm_node））;
			}

			idx?=?strtok（NULL“:“）;
			val?=?strtok（NULL“?\t“）;

			if（val?==?NULL）
				break;
			errno?=?0;
			x[i].index?=?（int）?strtol（idx&endptr10）;
			if（endptr?==?idx?||?errno?!=?0?||?*endptr?!=?‘\0‘?||?x[i].index?<=?inst_max_index）
				exit_input_error（total+1）;
			else
				inst_max_index?=?x[i].index;

			errno?=?0;
			x[i].value?=?strtod（val&endptr）;
			if（endptr?==?val?||?errno?!=?0?||?（*endptr?!=?‘\0‘?&&?!isspace（*endptr）））
				exit_input_error（total+1）;

			++i;
		}
		x[i].index?=?-1;

		if?（predict_probability?&&?（svm_type==C_SVC?||?svm_type==NU_SVC））
		{
			predict_label?=?svm_predict_probability（modelxprob_estimates）;
			fprintf（output“%g“predict_label）;
			for（j

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2018-08-12?10:33??libsvm-3.23\
?????文件????????1497??2018-07-15?22:16??libsvm-3.23\COPYRIGHT
?????文件???????83238??2018-07-15?22:16??libsvm-3.23\FAQ.html
?????文件???????27670??2018-07-15?22:16??libsvm-3.23\heart_scale
?????文件???????28904??2018-08-11?19:03??libsvm-3.23\heart_scale.mat
?????目錄???????????0??2018-08-12?10:22??libsvm-3.23\java\
?????目錄???????????0??2018-08-12?10:22??libsvm-3.23\java\libsvm\
?????文件???????55181??2018-07-15?22:17??libsvm-3.23\java\libsvm.jar
?????文件???????64084??2018-07-15?22:17??libsvm-3.23\java\libsvm\svm.java
?????文件???????63281??2018-07-15?22:16??libsvm-3.23\java\libsvm\svm.m4
?????文件?????????868??2018-07-15?22:16??libsvm-3.23\java\libsvm\svm_model.java
?????文件?????????115??2018-07-15?22:16??libsvm-3.23\java\libsvm\svm_node.java
?????文件????????1285??2018-07-15?22:16??libsvm-3.23\java\libsvm\svm_parameter.java
?????文件??????????87??2018-07-15?22:16??libsvm-3.23\java\libsvm\svm_print_interface.java
?????文件?????????136??2018-07-15?22:16??libsvm-3.23\java\libsvm\svm_problem.java
?????文件?????????659??2018-07-15?22:16??libsvm-3.23\java\Makefile
?????文件????????4945??2018-07-15?22:16??libsvm-3.23\java\svm_predict.java
?????文件????????8937??2018-07-15?22:16??libsvm-3.23\java\svm_scale.java
?????文件???????12262??2018-07-15?22:16??libsvm-3.23\java\svm_toy.java
?????文件????????8354??2018-07-15?22:16??libsvm-3.23\java\svm_train.java
?????文件??????????81??2018-07-15?22:16??libsvm-3.23\java\test_applet.html
?????文件?????????732??2018-07-15?22:16??libsvm-3.23\Makefile
?????文件????????1135??2018-07-15?22:16??libsvm-3.23\Makefile.win
?????目錄???????????0??2018-08-12?10:22??libsvm-3.23\matlab\
?????文件????????4060??2018-07-15?22:16??libsvm-3.23\matlab\libsvmread.c
?????文件????????2326??2018-07-15?22:16??libsvm-3.23\matlab\libsvmwrite.c
?????文件?????????888??2018-07-15?22:16??libsvm-3.23\matlab\make.m
?????文件????????1240??2018-07-15?22:16??libsvm-3.23\matlab\Makefile
?????文件????????9815??2018-07-15?22:16??libsvm-3.23\matlab\README
?????文件????????9818??2018-07-15?22:16??libsvm-3.23\matlab\svmpredict.c
?????文件???????11817??2018-07-15?22:16??libsvm-3.23\matlab\svmtrain.c
............此處省略37個文件信息