test_sc

 TEST_SC: apply statistical and SVM classifier to test data 

  R = test_sc(CC,D,TYPE [,target_Classlabel]) 
       R.output     output distance for each class
       R.classlabel class for output data
  The target class is optional. If it is provided, the following values are returned. 
       R.kappa Cohen's kappa coefficient
       R.ACC   Classification accuracy 
       R.H     Confusion matrix 

 The classifier CC is typically obtained by TRAIN_SC. If a statistical 
 classifier is used, TYPE can be used to modify the classifier. 
    TYPE = 'MDA'    mahalanobis distance based classifier
    TYPE = 'MD2'    mahalanobis distance based classifier
    TYPE = 'MD3'    mahalanobis distance based classifier
    TYPE = 'GRB'    Gaussian radial basis function 
    TYPE = 'QDA'    quadratic discriminant analysis
    TYPE = 'LD2'    linear discriminant analysis (see LDBC2)
    TYPE = 'LD3'    linear discriminant analysis (see LDBC3)
    TYPE = 'LD4'    linear discriminant analysis (see LDBC4)
    TYPE = 'GDBC'   general distance based classifier
 
 see also: TRAIN_SC

 References:
 [1] R. Duda, P. Hart, and D. Stork, Pattern Classification, second ed.
       John Wiley & Sons, 2001.