| @@ -0,0 +1,22 @@ | |||||
| // | |||||
| // svm_model | |||||
| // | |||||
| package libsvm; | |||||
| public class svm_model implements java.io.Serializable | |||||
| { | |||||
| public svm_parameter param; // parameter | |||||
| public int nr_class; // number of classes, = 2 in regression/one class svm | |||||
| public int l; // total #SV | |||||
| public svm_node[][] SV; // SVs (SV[l]) | |||||
| public double[][] sv_coef; // coefficients for SVs in decision functions (sv_coef[k-1][l]) | |||||
| public double[] rho; // constants in decision functions (rho[k*(k-1)/2]) | |||||
| public double[] probA; // pariwise probability information | |||||
| public double[] probB; | |||||
| public int[] sv_indices; // sv_indices[0,...,nSV-1] are values in [1,...,num_traning_data] to indicate SVs in the training set | |||||
| // for classification only | |||||
| public int[] label; // label of each class (label[k]) | |||||
| public int[] nSV; // number of SVs for each class (nSV[k]) | |||||
| // nSV[0] + nSV[1] + ... + nSV[k-1] = l | |||||
| }; | |||||