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  1. > source("copulas.R")
  2. > data <- rnorm2(10)
  3. > svm_train(data[,1], data[,2])
  4.  
  5. Call:
  6. svm.default(x = x, y = y, gamma = svmpar$best.parameters$gamma, nu = svmpar$best.parameters$nu)
  7.  
  8.  
  9. Parameters:
  10. SVM-Type: eps-regression
  11. SVM-Kernel: radial
  12. cost: 1
  13. gamma: 0.04978707
  14. epsilon: 0.1
  15.  
  16.  
  17. Number of Support Vectors: 8
  18.  
  19. > data <- rnorm2(10)
  20. > svm_train(data[,1], data[,2])
  21.  
  22. Call:
  23. svm.default(x = x, y = y, gamma = svmpar$best.parameters$gamma, nu = svmpar$best.parameters$nu)
  24.  
  25.  
  26. Parameters:
  27. SVM-Type: eps-regression
  28. SVM-Kernel: radial
  29. cost: 1
  30. gamma: 4.481689
  31. epsilon: 0.1
  32.  
  33.  
  34. Number of Support Vectors: 9
  35.  
  36. >
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