svm_model.java
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1 //
2 // svm_model
3 //
4 package libsvm;
5 public class svm_model implements java.io.Serializable
6 {
7  public svm_parameter param; // parameter
8  public int nr_class; // number of classes, = 2 in regression/one class svm
9  public int l; // total #SV
10  public svm_node[][] SV; // SVs (SV[l])
11  public double[][] sv_coef; // coefficients for SVs in decision functions (sv_coef[k-1][l])
12  public double[] rho; // constants in decision functions (rho[k*(k-1)/2])
13  public double[] probA; // pariwise probability information
14  public double[] probB;
15  public int[] sv_indices; // sv_indices[0,...,nSV-1] are values in [1,...,num_traning_data] to indicate SVs in the training set
16 
17  // for classification only
18 
19  public int[] label; // label of each class (label[k])
20  public int[] nSV; // number of SVs for each class (nSV[k])
21  // nSV[0] + nSV[1] + ... + nSV[k-1] = l
22 };
svm_parameter param
Definition: svm_model.java:7
svm_node [][] SV
Definition: svm_model.java:10
double [][] sv_coef
Definition: svm_model.java:11
double [] probA
Definition: svm_model.java:13
double [] probB
Definition: svm_model.java:14
double [] rho
Definition: svm_model.java:12


ml_classifiers
Author(s): Scott Niekum , Joshua Whitley
autogenerated on Mon Feb 28 2022 22:46:49