C++ 将matlab中的libsvm模型结构保存到.model文件中，该文件可以在C+中读取+；

我有两个问题：

我按照邮局的指示去做 我尝试在Mac OSx El Capitan上构建svm_savemodel.c，使用： mex svm_savemodel.c发生了以下情况：

使用“带叮当声的Xcode”构建。为架构x86\u 64使用mex未定义符号时出错：“\u matlab\u matrix\u to\u model”，引用自：svm\u savemodel.o中的\u mexFunction“\u svm\u free\u and \u destroy\u model”，引用自：svm\u savemodel中的\u mexFunction.o”\u svm\u savemodel中的\u mexFunction.o ld:symbol找不到体系结构x86_64 clang:错误：链接器命令失败，退出代码为1（使用-v查看调用） 有人能提出一些解决办法吗

所以我想编写一个MATLAB代码，将MATLAB中的模型结构转换成可以在C++中读取的MyMealth.Moad文件。 这篇文章讨论了需要保存在.model文件中的参数 我正在处理回归问题，因此在我的情况下，标签条目将不存在。除此之外还有什么我需要照顾的吗

谢谢。

我在上修改了用于回归的代码，并查看了保存模型的格式

{ struct svm_parameter param；//由parse_命令行设置 struct svm_problem prob；//由read_problem设置 //结构svm_模型*模型； 结构svm_节点*x_空间

int main(int argc, const char * argv[]) {
char input_file_name[1024];
char model_file_name[1024] = "MyModel" ;
const char *error_msg;

param.svm_type = EPSILON_SVR;
param.eps = 1e-3;
param.C = 1;
//param.kernel_type = RBF;
param.degree = 3;


//Problem definition-------------------------------------------------------------
prob.l = 8;

//x values matrix of xor values
double matrix[prob.l][2];
matrix[0][0] = 0.1;
matrix[0][1] = 0.2;

matrix[1][0] = 0.2;
matrix[1][1] = 0.3;

matrix[2][0] = 0.4;
matrix[2][1] = 0.5;

matrix[3][0] = 0.8;
matrix[3][1] = 0.9;

matrix[4][0] = 0.6;
matrix[4][1] = 0.7;

matrix[5][0] = 0.55;
matrix[5][1] = 0.65;

matrix[6][0] = 0.45;
matrix[6][1] = 0.55;

matrix[7][0] = 0.65;
matrix[7][1] = 0.75;

svm_node** x = Malloc(svm_node*,prob.l);

//Trying to assign from matrix to svm_node training examples
for (int row = 0;row <prob.l; row++){
    svm_node* x_space = Malloc(svm_node,3);
    for (int col = 0;col < 2;col++){
        x_space[col].index = col;
        x_space[col].value = matrix[row][col];
    }
    x_space[2].index = -1;      //Each row of properties should be terminated with a -1 according to the readme
    x[row] = x_space;
}

prob.x = x;

//yvalues
prob.y = Malloc(double,prob.l);
prob.y[0] = 0.15;
prob.y[1] = 0.25;
prob.y[2] = 0.45;
prob.y[3] = 0.85;
prob.y[4] = 0.65;
prob.y[5] = 0.6;
prob.y[6] = 0.5;
prob.y[7] = 0.7;

//Train model---------------------------------------------------------------------
svm_model *model = svm_train(&prob,&param);
//svm_model *model = svm_load_model(model_file_name);

//Test model----------------------------------------------------------------------
svm_node* testnode = Malloc(svm_node,3);
testnode[0].index = 0;
testnode[0].value = 0.6;
testnode[1].index = 1;
testnode[1].value = 0.7;
testnode[2].index = -1;

//This works correctly:
double retval = svm_predict(model,testnode);

    svm_save_model(model_file_name, model);
printf("retval: %f\n",retval);


svm_destroy_param(&param);
free(prob.y);
free(prob.x);
free(x_space);

return 0;

结束 fclose（fid）

}

我修改了处的回归代码，并查看了保存模型的格式

{ struct svm_parameter param；//由parse_命令行设置 struct svm_problem prob；//由read_problem设置 //结构svm_模型*模型； 结构svm_节点*x_空间

int main(int argc, const char * argv[]) {
char input_file_name[1024];
char model_file_name[1024] = "MyModel" ;
const char *error_msg;

param.svm_type = EPSILON_SVR;
param.eps = 1e-3;
param.C = 1;
//param.kernel_type = RBF;
param.degree = 3;


//Problem definition-------------------------------------------------------------
prob.l = 8;

//x values matrix of xor values
double matrix[prob.l][2];
matrix[0][0] = 0.1;
matrix[0][1] = 0.2;

matrix[1][0] = 0.2;
matrix[1][1] = 0.3;

matrix[2][0] = 0.4;
matrix[2][1] = 0.5;

matrix[3][0] = 0.8;
matrix[3][1] = 0.9;

matrix[4][0] = 0.6;
matrix[4][1] = 0.7;

matrix[5][0] = 0.55;
matrix[5][1] = 0.65;

matrix[6][0] = 0.45;
matrix[6][1] = 0.55;

matrix[7][0] = 0.65;
matrix[7][1] = 0.75;

svm_node** x = Malloc(svm_node*,prob.l);

//Trying to assign from matrix to svm_node training examples
for (int row = 0;row <prob.l; row++){
    svm_node* x_space = Malloc(svm_node,3);
    for (int col = 0;col < 2;col++){
        x_space[col].index = col;
        x_space[col].value = matrix[row][col];
    }
    x_space[2].index = -1;      //Each row of properties should be terminated with a -1 according to the readme
    x[row] = x_space;
}

prob.x = x;

//yvalues
prob.y = Malloc(double,prob.l);
prob.y[0] = 0.15;
prob.y[1] = 0.25;
prob.y[2] = 0.45;
prob.y[3] = 0.85;
prob.y[4] = 0.65;
prob.y[5] = 0.6;
prob.y[6] = 0.5;
prob.y[7] = 0.7;

//Train model---------------------------------------------------------------------
svm_model *model = svm_train(&prob,&param);
//svm_model *model = svm_load_model(model_file_name);

//Test model----------------------------------------------------------------------
svm_node* testnode = Malloc(svm_node,3);
testnode[0].index = 0;
testnode[0].value = 0.6;
testnode[1].index = 1;
testnode[1].value = 0.7;
testnode[2].index = -1;

//This works correctly:
double retval = svm_predict(model,testnode);

    svm_save_model(model_file_name, model);
printf("retval: %f\n",retval);


svm_destroy_param(&param);
free(prob.y);
free(prob.x);
free(x_space);

return 0;

结束 fclose（fid）

}