我使用LIBSVM以编程方式做一个简单的XOR分类，试图了解函数是如何工作的。 我有以下自述的说明尽可能靠近设置的问题。 我仍然使用svm_predict时得到错误的输出（始终为1或-1）。
在一个相关的问题，有人建议，使用很少的训练样本时可能出现的问题。 我试图提高了实例的个数，以20但这并没有帮助。
我怀疑，这个问题是某处prob.x和/或prob.y的定义，但可以不明白的地方。 你能帮助阐明如何界定prob.x和使用svm_node prob.y？
我哈得彻底搜查，但找不到答案......比如这里， 这里， 这里， 这里， 这里。
提前致谢！
这里是我的代码：
//Parameters
svm_parameter param;
param.svm_type = C_SVC;
param.kernel_type = RBF;
param.degree = 3;
param.gamma = 0;
param.coef0 = 0;
param.nu = 0.5;
param.cache_size = 100;
param.C = 0.4;
param.eps = 1e-3;
param.p = 0.1;
param.shrinking = 1;
param.probability = 0;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
//Problem definition
svm_problem prob;
//Length
prob.l = 4; //number of training examples
//x values
svm_node** x = new svm_node *[prob.l]; //Array of pointers to pointers to arrays
svm_node* x_space1 = new svm_node[3]; //Fist training example
svm_node* x_space2 = new svm_node[3]; //Second training example
svm_node* x_space3 = new svm_node[3]; //Third training example
svm_node* x_space4 = new svm_node[3]; //Fourth training example
x_space1[0].index = 1; //Fist training example
x_space1[0].value = 1;
x_space1[1].index = 2;
x_space1[1].value = 1;
x_space1[2].index = -1;
x_space2[0].index = 1; //Second training example
x_space2[0].value = 1;
x_space2[1].index = 2;
x_space2[1].value = 0;
x_space2[2].index = -1;
x_space3[0].index = 1; //Third training example
x_space3[0].value = 0;
x_space3[1].index = 2;
x_space3[1].value = 1;
x_space3[2].index = -1;
x_space4[0].index = 1; //Fourth training example
x_space4[0].value = 0;
x_space4[1].index = 2;
x_space4[1].value = 0;
x_space4[2].index = -1;
x[0] = x_space1; //Set each training example to x
x[1] = x_space2;
x[2] = x_space3;
x[3] = x_space4;
prob.x = x; //Assign x to the struct field prob.x
//yvalues
prob.y = new double[prob.l];
prob.y[0] = -1;
prob.y[1] = 1;
prob.y[2] = 1;
prob.y[3] = -1;
//Train model
svm_model *model = svm_train(&prob,¶m);
//Test model
svm_node* testnode = new svm_node[3];
testnode[0].index = 1;
testnode[0].value = 1;
testnode[1].index = 2;
testnode[1].value = 0;
testnode[2].index = -1;
double retval = svm_predict(model,testnode);
qDebug()<<retval; //Should return +1 but returns -1
