資源簡介
SVM分類器，可在行人檢測時用來分類訓(xùn)練樣本，在MATLAB中直接試用。
代碼片段和文件信息
#include?
#include?
#include?
#include?
#include?
#include?“svm.h“
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）
printf（“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“l(fā)abels“）;
for（j=0;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=0;j
fprintf（output“\n“）;
}
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????1497??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\COPYRIGHT
?????文件???????68901??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\FAQ.html
?????文件???????27670??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\heart_scale
?????文件?????????528??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\Makefile
?????文件????????1087??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\Makefile.win
?????文件???????26720??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\README
?????文件????????5381??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm-predict.c
?????文件????????7042??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm-scale.c
?????文件????????8891??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm-train.c
?????文件???????62509??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm.cpp
?????文件???????62509??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm.cpp.bak
?????文件?????????434??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm.def
?????文件????????3129??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\svm.h
?????文件???????49854??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm.jar
?????文件?????????624??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\Makefile
?????文件????????4267??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_predict.java
?????文件????????8944??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_scale.java
?????文件???????11483??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_toy.java
?????文件????????8268??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_train.java
?????文件??????????81??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\test_ap
?????文件???????61931??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm.java
?????文件???????61280??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm.m4
?????文件?????????734??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_model.java
?????文件?????????115??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_node.java
?????文件????????1288??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_parameter.java
?????文件??????????87??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_print_interface.java
?????文件?????????136??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_problem.java
?????文件???????28904??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\heart_scale.mat
?????文件????????3988??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmread.c
?????文件???????20480??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmread.mexw32
?????文件????????2123??2020-09-27?14:58??libsvm\libsvm3.1\libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmwrite.c
............此處省略126個文件信息
評論
共有 條評論