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svm_model.java 868 B

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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. // for classification only
  17. public int[] label; // label of each class (label[k])
  18. public int[] nSV; // number of SVs for each class (nSV[k])
  19. // nSV[0] + nSV[1] + ... + nSV[k-1] = l
  20. };

A Python package for graph kernels, graph edit distances and graph pre-image problem.