Demo SVM
Demos you can play with
Thanks to the gaml library and its gaml-libsvm wrapper with libsvm, you can experiment SVMs easily. To do so, download and uncompress DemoLibSVM-003.tar.gz. The following are examples of what you can get.
Classification
#define NB_SAMPLES    1000
#define SPACE_FILTER  filter_blobs
#define ORACLE        oracle_split

#define MISCLASSIFICATION_RATIO 0

  params.svm_type    = C_SVC;
  params.kernel_type = LINEAR; 
  params.C           = 1;
  params.eps         = 1e-8; // numerical tolerence
        
  params.C           = .001;
        
  params.svm_type    = NU_SVC;
  params.nu          = .2;
        
#define NB_SAMPLES     1000
#define SPACE_FILTER   filter_true
#define ORACLE         oracle_checker
#define CHECKER_PERIOD .1 
#define MISCLASSIFICATION_RATIO 0

  params.svm_type    = NU_SVC;
  params.nu          = .1; 
  params.kernel_type = POLY;
  params.gamma       = 1;  
  params.degree      = 3;
  params.coef0       = 1;
        
  params.svm_type    = NU_SVC;
  params.nu          = .1; 
  params.kernel_type = RBF;
  params.gamma       = 1; 
        
#define CHECKER_PERIOD 1 
        
#define NB_SAMPLES     100
        
  params.gamma       = 10; 
        
One-class
#define NB_SAMPLES    100
#define SPACE_FILTER  filter_blobs

  params.svm_type    = ONE_CLASS;
  params.kernel_type = RBF;
  params.gamma       = .05; 
  params.nu          = .05;
  params.eps         = 1e-8; // numerical tolerence
        
#define SPACE_FILTER  filter_banana

  params.gamma       = .1; 
        
Regression 1D
#define NB_SAMPLES      100
#define ORACLE          oracle_line
#define NOISE_AMPLITUDE 0

  params.svm_type    = EPSILON_SVR;
  params.kernel_type = LINEAR; 
  params.p           = .2;  // epsilon
  params.C           =  1;
  params.eps         = 1e-8; // numerical tolerence
        
#define ORACLE          oracle_sinus
#define NOISE_AMPLITUDE 0.2
        
  params.kernel_type = POLY; 
  params.gamma       = 1;  
  params.degree      = 3;
  params.coef0       = 1;
        
  params.kernel_type = RBF; 
  params.gamma       = 1;  
        
#define NB_SAMPLES     10

  params.kernel_type = RBF; 
  params.gamma       = 10;  
        
Regression 2D
#define NB_SAMPLES      150
#define ORACLE          oracle_wave
#define NOISE_AMPLITUDE 0
  params.svm_type    = EPSILON_SVR;
  params.kernel_type = RBF; 
  params.gamma       = .75;  
  params.p           = .2;  // epsilon
  params.C           =  1;
  params.eps         = 1e-8; // numerical tolerence
        
  params.svm_type    = NU_SVR;
  params.nu          = .5; 
        
#define NOISE_AMPLITUDE 0.1
        
Misc
Effect of C and σ on classification
When C varies

When σ varies