// Training SVM with feature vector X and label Y.
// Each row of X is a feature vector, with corresponding label in Y.
// Return a CV_32F weight Mat
Mat Objectness::trainSVM(CMat &X1f, const vecI &Y, int sT, double C, double bias, double eps)
{
// Set SVM parameters
parameter param; {
param.solver_type = sT; // L2R_L2LOSS_SVC_DUAL;
param.C = C;
param.eps = eps; // see setting below
param.p = 0.1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
set_print_string_function(print_null);
CV_Assert(X1f.rows == Y.size() && X1f.type() == CV_32F);
}
// Initialize a problem
feature_node *x_space = NULL;
problem prob;{
prob.l = X1f.rows;
prob.bias = bias;
prob.y = Malloc(double, prob.l);
prob.x = Malloc(feature_node*, prob.l);
const int DIM_FEA = X1f.cols;
prob.n = DIM_FEA + (bias >= 0 ? 1 : 0);
x_space = Malloc(feature_node, (prob.n + 1) * prob.l);
int j = 0;
for (int i = 0; i < prob.l; i++){
prob.y[i] = Y[i];
prob.x[i] = &x_space[j];
const float* xData = X1f.ptr<float>(i);
for (int k = 0; k < DIM_FEA; k++){
x_space[j].index = k + 1;
x_space[j++].value = xData[k];
}
if (bias >= 0){
x_space[j].index = prob.n;
x_space[j++].value = bias;
}
x_space[j++].index = -1;
}
CV_Assert(j == (prob.n + 1) * prob.l);
}
// Training SVM for current problem
const char* error_msg = check_parameter(&prob, ¶m);
if(error_msg){
fprintf(stderr,"ERROR: %s\n",error_msg);
exit(1);
}
model *svmModel = train(&prob, ¶m);
Mat wMat(1, prob.n, CV_64F, svmModel->w);
wMat.convertTo(wMat, CV_32F);
free_and_destroy_model(&svmModel);
destroy_param(¶m);
free(prob.y);
free(prob.x);
free(x_space);
return wMat;
}
void set_default_params(){
void (*print_func)(const char*) = NULL; // default printing to stdout
// default values
param.solver_type = L2R_LR; //L2R_LR_DUAL;//L1R_LR;//
param.C = 1;
param.eps = INF; // see setting below
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
flag_cross_validation = 1;
bias = -1;
set_print_string_function(print_func);
if(param.eps == INF){
if(param.solver_type == L2R_LR || param.solver_type == L2R_L2LOSS_SVC)
param.eps = 0.01;
else if(param.solver_type == L2R_L2LOSS_SVC_DUAL || param.solver_type == L2R_L1LOSS_SVC_DUAL || param.solver_type == MCSVM_CS || param.solver_type == L2R_LR_DUAL)
param.eps = 0.1;
else if(param.solver_type == L1R_L2LOSS_SVC || param.solver_type == L1R_LR)
param.eps = 0.01;
}
}
void parse_command_line(int argc, char **argv, char *input_file_name, char *model_file_name)
{
int i;
void (*print_func)(const char*) = NULL; // default printing to stdout
// default values
param.solver_type = L2R_L2LOSS_SVC_DUAL;
param.C = 1;
param.eps = INF; // see setting below
param.p = 0.1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
param.init_sol = NULL;
flag_cross_validation = 0;
flag_warm_start = 0;
flag_C_specified = 0;
flag_solver_specified = 0;
flag_find_C = 0;
bias = -1;
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
if(++i>=argc)
exit_with_help();
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
flag_solver_specified = 1;
break;
case 'c':
param.C = atof(argv[i]);
flag_C_specified = 1;
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'v':
flag_cross_validation = 1;
nr_fold = atoi(argv[i]);
if(nr_fold < 2)
{
fprintf(stderr,"n-fold cross validation: n must >= 2\n");
exit_with_help();
}
break;
case 'q':
print_func = &print_null;
i--;
break;
case 'i':
flag_warm_start = 1;
if((initial_model=load_model(argv[i]))==0)
{
fprintf(stderr,"can't open initial model file %s\n",argv[i]);
exit_with_help();
}
break;
case 'C':
flag_find_C = 1;
i--;
break;
default:
fprintf(stderr,"unknown option: -%c\n", argv[i-1][1]);
exit_with_help();
break;
}
}
if(flag_warm_start)
{
if(param.solver_type != L2R_LR && param.solver_type != L2R_L2LOSS_SVC)
{
fprintf(stderr,"-i is supported only for -s 0 and 2\n");
exit(1);
}
if(param.solver_type != initial_model->param.solver_type)
fprintf(stderr,"Warning: the solver type of initial model dose not match your -s option\n");
}
set_print_string_function(print_func);
// determine filenames
if(i>=argc)
exit_with_help();
strcpy(input_file_name, argv[i]);
if(i<argc-1)
strcpy(model_file_name,argv[i+1]);
else
{
char *p = strrchr(argv[i],'/');
if(p==NULL)
p = argv[i];
else
++p;
sprintf(model_file_name,"%s.model",p);
}
// default solver for parameter selection is L2R_L2LOSS_SVC
if(flag_find_C)
{
if(!flag_cross_validation)
nr_fold = 5;
if(!flag_solver_specified)
{
fprintf(stderr, "Solver not specified. Using -s 2\n");
param.solver_type = L2R_L2LOSS_SVC;
}
else if(param.solver_type != L2R_LR && param.solver_type != L2R_L2LOSS_SVC)
{
fprintf(stderr, "Warm-start parameter search only available for -s 0 and -s 2\n");
exit_with_help();
}
}
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_LR:
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
param.eps = 0.001;
break;
case L2R_L2LOSS_SVC_DUAL:
case L2R_L1LOSS_SVC_DUAL:
case MCSVM_CS:
case L2R_LR_DUAL:
param.eps = 0.1;
break;
case L1R_L2LOSS_SVC:
case L1R_LR:
param.eps = 0.01;
break;
case L2R_L1LOSS_SVR_DUAL:
case L2R_L2LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
}
}
void parse_command_line(int argc, char **argv, char *input_file_name, char *model_file_name)
{
int i;
void (*print_func)(const char*) = NULL; // default printing to stdout
// default values
param.solver_type = L2R_L2LOSS_SVC_DUAL;
param.C = 1;
param.eps = INF; // see setting below
param.p = 0.1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
param.concurrency = 1;
flag_cross_validation = 0;
bias = -1;
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
if(++i>=argc)
exit_with_help();
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
break;
case 'c':
param.C = atof(argv[i]);
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'v':
flag_cross_validation = 1;
nr_fold = atoi(argv[i]);
if(nr_fold < 2)
{
fprintf(stderr,"n-fold cross validation: n must >= 2\n");
exit_with_help();
}
break;
case 'q':
print_func = &print_null;
i--;
break;
case 'n':
param.concurrency = atoi(argv[i]);
break;
default:
fprintf(stderr,"unknown option: -%c\n", argv[i-1][1]);
exit_with_help();
break;
}
}
set_print_string_function(print_func);
// determine filenames
if(i>=argc)
exit_with_help();
strcpy(input_file_name, argv[i]);
if(i<argc-1)
strcpy(model_file_name,argv[i+1]);
else
{
char *p = strrchr(argv[i],'/');
if(p==NULL)
p = argv[i];
else
++p;
sprintf(model_file_name,"%s.model",p);
}
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_LR:
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
param.eps = 0.001;
break;
case L2R_L2LOSS_SVC_DUAL:
case L2R_L1LOSS_SVC_DUAL:
case MCSVM_CS:
case L2R_LR_DUAL:
param.eps = 0.1;
break;
case L1R_L2LOSS_SVC:
case L1R_LR:
param.eps = 0.01;
break;
case L2R_L1LOSS_SVR_DUAL:
case L2R_L2LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
}
}
/* provide convenience wrapper */
void set_verbosity(int verbosity_flag){
if (verbosity_flag)
set_print_string_function(&print_string_stdout);
else
set_print_string_function(&print_null);
}
cv::Mat_<double> cRegression::__train_regressor(const cv::Mat_<double>& label_vec, const cv::Mat_<int>& instance_mat)
{
void(*print_func)(const char*) = &print_null;
const char *error_msg;
struct parameter param;
struct problem problem;
struct feature_node *x_space = NULL;
srand(1);
// std::cout << "initialize liblinear parameter." << std::endl;
param.solver_type = L2R_L2LOSS_SVR_DUAL;
param.C = 1.0 / (double)label_vec.rows;
param.eps = 0.1;
param.p = 0;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
// std::cout << "initialize liblinear parameter finished." << std::endl;
set_print_string_function(print_func);
std::vector<int>* prob_x = NULL;
prob_x = new std::vector<int>[label_vec.rows]; // number of samples = label_vec.rows
size_t nzcount = 0;
// std::cout << "copy feature." << std::endl;
for (int i = 0; i < instance_mat.rows; ++i) {
for (int j = 0; j < instance_mat.cols; ++j) {
int elem = instance_mat(i, j);
if (elem != 0) {
prob_x[i].push_back(j);
++nzcount;
}
}
}
// std::cout << "copy feature finished." << std::endl;
//sort the vector
for (int i = 0; i < label_vec.rows; i++){
std::sort(prob_x[i].begin(), prob_x[i].end());
}
problem.l = label_vec.rows;
problem.n = instance_mat.cols;
problem.bias = -1;
int elements = (int)(nzcount + problem.l);
problem.y = Malloc(double, problem.l);
problem.x = Malloc(struct feature_node *, problem.l);
x_space = Malloc(struct feature_node, elements);
int j = 0;
for (int i = 0; i < problem.l; i++){
problem.y[i] = label_vec(i, 0);
problem.x[i] = &x_space[j];
for (int k = 0; k < prob_x[i].size(); k++){
x_space[j].index = prob_x[i][k] + 1;
x_space[j].value = 1;
j++;
}
x_space[j++].index = -1;
}
delete[] prob_x;
error_msg = check_parameter(&problem, ¶m);
if (error_msg){
fprintf(stderr, "ERROR: %s\n", error_msg);
}
// std::cout << "train model." << std::endl;
struct model *model = NULL;
model = train(&problem, ¶m);
// std::cout << "train model finished." << std::endl;
cv::Mat_<double> weight = cv::Mat::zeros(model->nr_feature, 1, CV_64FC1);
for (int i = 0; i < model->nr_feature; i++){
weight(i, 0) = model->w[i];
// std::cout << weight(i, 0) << " "; // std::endl;
}
free_and_destroy_model(&model);
destroy_param(¶m);
free((void*)(problem.y));
free((void*)(problem.x));
free((void*)(x_space));
return weight;
}
// nrhs should be 3
int parse_command_line(int nrhs, const mxArray *prhs[], char *model_file_name)
{
int i, argc = 1;
char cmd[CMD_LEN];
char *argv[CMD_LEN/2];
void (*print_func)(const char *) = print_string_matlab; // default printing to matlab display
// default values
param.solver_type = L2R_L2LOSS_SVC_DUAL;
param.C = 1;
param.eps = INF; // see setting below
param.p = 0.1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
cross_validation_flag = 0;
col_format_flag = 0;
bias = -1;
if(nrhs <= 1)
return 1;
if(nrhs == 4)
{
mxGetString(prhs[3], cmd, mxGetN(prhs[3])+1);
if(strcmp(cmd, "col") == 0)
col_format_flag = 1;
}
// put options in argv[]
if(nrhs > 2)
{
mxGetString(prhs[2], cmd, mxGetN(prhs[2]) + 1);
if((argv[argc] = strtok(cmd, " ")) != NULL)
while((argv[++argc] = strtok(NULL, " ")) != NULL)
;
}
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
++i;
if(i>=argc && argv[i-1][1] != 'q') // since option -q has no parameter
return 1;
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
break;
case 'c':
param.C = atof(argv[i]);
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'v':
cross_validation_flag = 1;
nr_fold = atoi(argv[i]);
if(nr_fold < 2)
{
mexPrintf("n-fold cross validation: n must >= 2\n");
return 1;
}
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'q':
print_func = &print_null;
i--;
break;
default:
mexPrintf("unknown option\n");
return 1;
}
}
set_print_string_function(print_func);
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_LR:
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
param.eps = 0.001;
break;
case L2R_L2LOSS_SVC_DUAL:
case L2R_L1LOSS_SVC_DUAL:
case MCSVM_CS:
case L2R_LR_DUAL:
param.eps = 0.1;
break;
case L1R_L2LOSS_SVC:
case L1R_LR:
param.eps = 0.01;
break;
case L2R_L1LOSS_SVR_DUAL:
case L2R_L2LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
}
return 0;
}
void parse_command_line(int argc, char **argv, char *input_file_name, char *model_file_name)
#endif
{
int i;
void (*print_func)(const char*) = NULL; // default printing to stdout
// default values
param.solver_type = AVLTREE ;//L2R_L2LOSS_SVC
param.C = 1;
param.eps = INF; // see setting below
param.p = 0;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
param.col_size = 50;//default
param.ite = 200;//default
param.eta = 1e-6;//default
param.batch_size = 10;
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
if(++i>=argc)
exit_with_help();
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
break;
case 'C':
param.C = atof(argv[i]);
break;
case 'c':
param.col_size = (int)atof(argv[i]);
break;
case 'l':
param.col_size =(int) atof(argv[i]);
break;
case 'b':
param.batch_size =(int) atof(argv[i]);
break;
case 'i':
param.ite = (int)atof(argv[i]);
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eta = atof(argv[i]);
break;
case 'q':
print_func = &print_null;
i--;
break;
default:
fprintf(stderr,"unknown option: -%c\n", argv[i-1][1]);
exit_with_help();
break;
}
}
set_print_string_function(print_func);
// determine filenames
if(i>=argc)
exit_with_help();
strcpy(input_file_name, argv[i]);
#ifdef FIGURE56
if(i<argc-1)
strcpy(test_file_name,argv[i+1]);
else
{
exit_with_help();
}
#else
if(i<argc-1)
strcpy(model_file_name,argv[i+1]);
else
{
//strrchr() 函数查找字符在指定字符串中从后面开始的第一次出现的位置，如果成功，则返回从该位置到字符串结尾的所有字符，如果失败，则返回 false。
//与之相对应的是strchr()函数，它查找字符串中首次出现指定字符的位置。
char *p = strrchr(argv[i],'/');
if(p==NULL)//there are no parent directories in the path of train data, that means train data are in the current directory
p = argv[i];
else//the train data contain parent directoryis, ++p: the pointer move from char '/' to the first char of the input train data
++p;
sprintf(model_file_name,"%s.model",p);//int sprintf ( char * str, const char * format, ... );Write formatted data to string
}
#endif
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
case WX_RBTREE:
case Y_RBTREE:
case AVLTREE:
case AATREE:
case DIRECT_COUNT:
case SELECTION_TREE:
case PRSVMP:
param.eps = 0.001;
break;
case L2R_L1LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
}
}
// nrhs should be 3
int parse_command_line(int nrhs, const mxArray *prhs[], char *model_file_name)
{
int i, argc = 1;
char cmd[CMD_LEN];
char *argv[CMD_LEN/2];
void (*print_func)(const char *) = print_string_matlab; // default printing to matlab display
// default values
param.solver_type = L2R_L2LOSS_SVC_DUAL;
param.C = 1;
param.eps = INF; // see setting below
param.p = 0.1;
param.nr_thread = 1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
param.init_sol = NULL;
flag_cross_validation = 0;
col_format_flag = 0;
flag_C_specified = 0;
flag_solver_specified = 0;
flag_find_C = 0;
flag_omp = 0;
bias = -1;
if(nrhs <= 1)
return 1;
if(nrhs == 4)
{
mxGetString(prhs[3], cmd, mxGetN(prhs[3])+1);
if(strcmp(cmd, "col") == 0)
col_format_flag = 1;
}
// put options in argv[]
if(nrhs > 2)
{
mxGetString(prhs[2], cmd, mxGetN(prhs[2]) + 1);
if((argv[argc] = strtok(cmd, " ")) != NULL)
while((argv[++argc] = strtok(NULL, " ")) != NULL)
;
}
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
++i;
if(i>=argc && argv[i-1][1] != 'q' && argv[i-1][1] != 'C') // since options -q and -C have no parameter
return 1;
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
flag_solver_specified = 1;
break;
case 'c':
param.C = atof(argv[i]);
flag_C_specified = 1;
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'n':
flag_omp = 1;
param.nr_thread = atoi(argv[i]);
break;
case 'v':
flag_cross_validation = 1;
nr_fold = atoi(argv[i]);
if(nr_fold < 2)
{
mexPrintf("n-fold cross validation: n must >= 2\n");
return 1;
}
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'q':
print_func = &print_null;
i--;
break;
case 'C':
flag_find_C = 1;
i--;
break;
default:
mexPrintf("unknown option\n");
return 1;
}
}
set_print_string_function(print_func);
// default solver for parameter selection is L2R_L2LOSS_SVC
if(flag_find_C)
{
if(!flag_cross_validation)
nr_fold = 5;
if(!flag_solver_specified)
{
mexPrintf("Solver not specified. Using -s 2\n");
param.solver_type = L2R_L2LOSS_SVC;
}
else if(param.solver_type != L2R_LR && param.solver_type != L2R_L2LOSS_SVC)
{
mexPrintf("Warm-start parameter search only available for -s 0 and -s 2\n");
return 1;
}
}
//default solver for parallel execution is L2R_L2LOSS_SVC
if(flag_omp)
{
if(!flag_solver_specified)
{
mexPrintf("Solver not specified. Using -s 2\n");
param.solver_type = L2R_L2LOSS_SVC;
}
else if(param.solver_type != L2R_LR &&
param.solver_type != L2R_L2LOSS_SVC &&
param.solver_type != L2R_L2LOSS_SVR &&
param.solver_type != L2R_L1LOSS_SVC_DUAL &&
param.solver_type != L2R_L2LOSS_SVC_DUAL)
{
mexPrintf("Parallel LIBLINEAR is only available for -s 0, 1, 2, 3, 11 now.\n");
return 1;
}
#ifndef CV_OMP
mexPrintf("Total threads used: %d\n", param.nr_thread);
#endif
}
#ifdef CV_OMP
if(flag_cross_validation)
{
int cvthreads = nr_fold;
int maxthreads = omp_get_num_procs();
if(flag_omp)
{
omp_set_nested(1);
maxthreads = omp_get_num_procs()/param.nr_thread;
}
if(cvthreads > maxthreads)
cvthreads = maxthreads;
omp_set_num_threads(cvthreads);
mexPrintf("Total threads used: %d\n", cvthreads*param.nr_thread);
}
#endif
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_LR:
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
param.eps = 0.001;
break;
case L2R_L2LOSS_SVC_DUAL:
case L2R_L1LOSS_SVC_DUAL:
case MCSVM_CS:
case L2R_LR_DUAL:
param.eps = 0.1;
break;
case L1R_L2LOSS_SVC:
case L1R_LR:
param.eps = 0.01;
break;
case L2R_L1LOSS_SVR_DUAL:
case L2R_L2LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
}
return 0;
}
void parse_command_line(int argc, char **argv)
{
int i;
void (*print_func)(const char*) = NULL; // default printing to stdout
char input_file_name[1024];
char test_file_name[1024];
// default values
param.solver_type = L2R_L2LOSS_SVC_DUAL;
param.C = 1;
param.eps = INF; // see setting below
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
bias = -1;
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
if(++i>=argc)
exit_with_help();
switch(argv[i-1][1])
{
case 'b':
flag_predict_probability = atoi(argv[i]);
break;
case 's':
param.solver_type = atoi(argv[i]);
break;
case 'c':
param.C = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'q':
print_func = &print_null;
i--;
break;
case 'r':
nb_runs = atoi(argv[i]);
break;
case 'l':
trnsz = atoi(argv[i]);
break;
default:
fprintf(stderr,"unknown option: -%c\n", argv[i-1][1]);
exit_with_help();
break;
}
}
set_print_string_function(print_func);
// determine filenames
if(i+2>=argc)
exit_with_help();
printf("reading train file %s\n",argv[i]);
strcpy(input_file_name, argv[i]);
prob=read_problem(input_file_name);
printf("reading test file %s\n",argv[i+1]);
strcpy(test_file_name, argv[i+1]);
tprob=read_problem(test_file_name);
output = fopen(argv[i+2],"a");
if(output == NULL)
{
fprintf(stderr,"can't open output file %s\n",argv[i+2]);
exit(1);
}
if(param.eps == INF)
{
if(param.solver_type == L2R_LR || param.solver_type == L2R_L2LOSS_SVC)
param.eps = 0.01;
else if(param.solver_type == L2R_L2LOSS_SVC_DUAL || param.solver_type == L2R_L1LOSS_SVC_DUAL || param.solver_type == MCSVM_CS)
param.eps = 0.1;
else if(param.solver_type == L1R_L2LOSS_SVC || param.solver_type == L1R_LR)
param.eps = 0.01;
}
}
void parse_command_line(int argc, char **argv, char *input_file_name, char *model_file_name)
{
int i;
void (*print_func)(const char*) = NULL; // default printing to stdout
// default values
param.solver_type = L2R_L2LOSS_SVC_DUAL;
param.C = 1;
param.eps = INF; // see setting below
param.p = 0.1;
param.nr_thread = 1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
param.init_sol = NULL;
flag_cross_validation = 0;
flag_C_specified = 0;
flag_solver_specified = 0;
flag_find_C = 0;
flag_omp = 0;
bias = -1;
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
if(++i>=argc)
exit_with_help();
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
flag_solver_specified = 1;
break;
case 'c':
param.C = atof(argv[i]);
flag_C_specified = 1;
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'n':
flag_omp = 1;
param.nr_thread = atoi(argv[i]);
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'v':
flag_cross_validation = 1;
nr_fold = atoi(argv[i]);
if(nr_fold < 2)
{
fprintf(stderr,"n-fold cross validation: n must >= 2\n");
exit_with_help();
}
break;
case 'q':
print_func = &print_null;
i--;
break;
case 'C':
flag_find_C = 1;
i--;
break;
default:
fprintf(stderr,"unknown option: -%c\n", argv[i-1][1]);
exit_with_help();
break;
}
}
set_print_string_function(print_func);
// determine filenames
if(i>=argc)
exit_with_help();
strcpy(input_file_name, argv[i]);
if(i<argc-1)
strcpy(model_file_name,argv[i+1]);
else
{
char *p = strrchr(argv[i],'/');
if(p==NULL)
p = argv[i];
else
++p;
sprintf(model_file_name,"%s.model",p);
}
// default solver for parameter selection is L2R_L2LOSS_SVC
if(flag_find_C)
{
if(!flag_cross_validation)
nr_fold = 5;
if(!flag_solver_specified)
{
fprintf(stderr, "Solver not specified. Using -s 2\n");
param.solver_type = L2R_L2LOSS_SVC;
}
else if(param.solver_type != L2R_LR && param.solver_type != L2R_L2LOSS_SVC)
{
fprintf(stderr, "Warm-start parameter search only available for -s 0 and -s 2\n");
exit_with_help();
}
}
//default solver for parallel execution is L2R_L2LOSS_SVC
if(flag_omp)
{
if(!flag_solver_specified)
{
fprintf(stderr, "Solver not specified. Using -s 2\n");
param.solver_type = L2R_L2LOSS_SVC;
}
else if(param.solver_type != L2R_LR && param.solver_type != L2R_L2LOSS_SVC && param.solver_type != L2R_L2LOSS_SVR)
{
fprintf(stderr, "Parallel LIBLINEAR is only available for -s 0, 2, 11 now\n");
exit_with_help();
}
#ifndef CV_OMP
printf("Total threads used: %d\n", param.nr_thread);
#endif
}
#ifdef CV_OMP
if(flag_cross_validation)
{
int cvthreads = nr_fold;
int maxthreads = omp_get_num_procs();
if(flag_omp)
{
omp_set_nested(1);
maxthreads = omp_get_num_procs()/param.nr_thread;
}
if(cvthreads > maxthreads)
cvthreads = maxthreads;
omp_set_num_threads(cvthreads);
printf("Total threads used: %d\n", cvthreads*param.nr_thread);
}
#endif
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_LR:
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
param.eps = 0.001;
break;
case L2R_L2LOSS_SVC_DUAL:
case L2R_L1LOSS_SVC_DUAL:
case MCSVM_CS:
case L2R_LR_DUAL:
param.eps = 0.1;
break;
case L1R_L2LOSS_SVC:
case L1R_LR:
param.eps = 0.01;
break;
case L2R_L1LOSS_SVR_DUAL:
case L2R_L2LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
}
}
void LVlinear_set_logging_userevent(lvError *lvErr, LVUserEventRef *loggingUserEvent_in) {
loggingUsrEv = loggingUserEvent_in;
set_print_string_function(LVlinear_print_function);
}
void parse_command_line(int argc, char **argv, char *input_file_name, char *model_file_name)
{
int i;
void (*print_func)(const char*) = NULL; // default printing to stdout
// default values
param.solver_type = MMCD;
param.C = 1;
param.eps = INF; // see setting below
param.p = 0.1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
flag_cross_validation = 0;
bias = -1;
param.reg_param = 1; // L2 regularizer
param.loss_param = 0.5; // tau for HU1, HU2
param.curv_param = 1e-3; // epsilon for minimum curvature value for NC
param.loss_type = HU2; // Huberized-hinge loss
param.curv_type = OC; // optimal curv
param.turn_to_nc = 0;
param.save_each_iter = 0;
param.init_model_file = NULL;
param.chat_level = 0; // minimal talk
param.cg_tol = 0.001;
param.cd_tol = 0.01;
param.cd_reset = 10;
param.structured_w = 0;
param.transform_matrix = 0;
param.tmx_c = 0;
param.tmx_r = 0;
// parse options
for(i=1;i<argc;i++)
{
if(argv[i][0] != '-') break;
if(++i>=argc)
exit_with_help();
switch(argv[i-1][1])
{
case 's':
param.solver_type = atoi(argv[i]);
break;
case 'c':
param.C = atof(argv[i]);
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'B':
bias = atof(argv[i]);
break;
case 'w':
++param.nr_weight;
param.weight_label = (int *) realloc(param.weight_label,sizeof(int)*param.nr_weight);
param.weight = (double *) realloc(param.weight,sizeof(double)*param.nr_weight);
param.weight_label[param.nr_weight-1] = atoi(&argv[i-1][2]);
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
case 'v':
flag_cross_validation = 1;
nr_fold = atoi(argv[i]);
if(nr_fold < 2)
{
fprintf(stderr,"n-fold cross validation: n must >= 2\n");
exit_with_help();
}
break;
case 'q':
print_func = &print_null;
i--;
break;
case 'l':
param.loss_type = (loss_var) atoi(argv[i]);
break;
case 'u':
if(atoi(argv[i]) < 3)
{
param.curv_type = (curv_var) atoi(argv[i]);
param.turn_to_nc = 0;
}
else if(atoi(argv[i]) == 3)
{
param.curv_type = (curv_var) 0;
param.turn_to_nc = 1;
}
else if(atoi(argv[i]) == 4)
{
param.curv_type = (curv_var) 1;
param.turn_to_nc = 1;
}
break;
case 'r':
param.reg_param = atof(argv[i]);
break;
case 'd':
param.cd_tol = atof(argv[i]);
break;
case 'f':
param.cd_reset = atoi(argv[i]);
break;
case 'g':
param.cg_tol = atof(argv[i]);
break;
case 'x':
param.test_file = Malloc(char,1024);
strcpy(param.test_file, argv[i]);
break;
case 't':
param.loss_param = atof(argv[i]);
break;
case 'n':
param.curv_param = atof(argv[i]);
break;
case 'i':
param.init_model_file = Malloc(char,1024);
strcpy(param.init_model_file, argv[i]);
break;
case 'h':
param.chat_level = atoi(argv[i]);
break;
case 'S':
if(strcmp(argv[i],"s")==0 || strcmp(argv[i],"a")==0)
{
param.structured_w = argv[i][0];
printf("\nUsing symmetric or asymmetric matrix as %c\n",param.structured_w);
}
else
{
param.transform_matrix = read_transform_matrix(argv[i],param.tmx_r,param.tmx_c);
param.structured_w = 'f';
printf("\nUsing free transform matrix %s\n",argv[i]);
}
break;
case 'X':
param.save_each_iter = Malloc(char,1024);
strcpy(param.save_each_iter, argv[i]);
break;
default:
fprintf(stderr,"unknown option: -%c\n", argv[i-1][1]);
exit_with_help();
break;
}
}
set_print_string_function(print_func);
// determine filenames
if(i>=argc)
exit_with_help();
strcpy(input_file_name, argv[i]);
if(i<argc-1)
strcpy(model_file_name,argv[i+1]);
else
{
char *p = strrchr(argv[i],'/');
if(p==NULL)
p = argv[i];
else
++p;
sprintf(model_file_name,"%s.model",p);
}
if(param.eps == INF)
{
switch(param.solver_type)
{
case L2R_LR:
case L2R_L2LOSS_SVC:
param.eps = 0.01;
break;
case L2R_L2LOSS_SVR:
param.eps = 0.001;
break;
case L2R_L2LOSS_SVC_DUAL:
case L2R_L1LOSS_SVC_DUAL:
case MCSVM_CS:
case L2R_LR_DUAL:
param.eps = 0.1;
break;
case L1R_L2LOSS_SVC:
case L1R_LR:
param.eps = 0.01;
break;
case L2R_L1LOSS_SVR_DUAL:
case L2R_L2LOSS_SVR_DUAL:
param.eps = 0.1;
break;
}
if(param.solver_type == MMCD ||param.solver_type == MMCD_SM || param.solver_type == MMCD_SG || param.solver_type == MMCD_SIMPLE || param.solver_type == MMGCD || param.solver_type == MMCG )
param.eps = 0.01;
}
}
