00001 // 00002 // svm_model 00003 // 00004 package libsvm; 00005 public class svm_model implements java.io.Serializable 00006 { 00007 public svm_parameter param; // parameter 00008 public int nr_class; // number of classes, = 2 in regression/one class svm 00009 public int l; // total #SV 00010 public svm_node[][] SV; // SVs (SV[l]) 00011 public double[][] sv_coef; // coefficients for SVs in decision functions (sv_coef[k-1][l]) 00012 public double[] rho; // constants in decision functions (rho[k*(k-1)/2]) 00013 public double[] probA; // pariwise probability information 00014 public double[] probB; 00015 public int[] sv_indices; // sv_indices[0,...,nSV-1] are values in [1,...,num_traning_data] to indicate SVs in the training set 00016 00017 // for classification only 00018 00019 public int[] label; // label of each class (label[k]) 00020 public int[] nSV; // number of SVs for each class (nSV[k]) 00021 // nSV[0] + nSV[1] + ... + nSV[k-1] = l 00022 };