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dml.svm
  svm support vector machine.
 
  DESCRIPTION
  Linear support vector machine classifier
 
    EXAMPLE
    X = rand(10,20); Y = [1 1 1 1 1 2 2 2 2 2]';
    m = dml.svm
    m = m.train(X,Y);
    Z = m.test(X);
 
    DEVELOPER
    Jason Farquhar (j.farquhar@donders.ru.nl)
Class Details
Superclasses dml.method
Sealed false
Construct on load false
Constructor Summary
svm support vector machine. 
Property Summary
C regularization parameter 
Ktest precomputed kernel for test data 
Ktrain precomputed kernel for training data 
X training data 
distance return distance from decision boundary instead of class label 
dual weights in dual form 
indims dimensions of the input data (excluding the trial dim and time dim in time series data) 
native uses native Bioinformatics toolbox SVM implementation if true 
primal weights in primal form 
restart when false, starts at the previously learned parameters; needed for online learning and grid search 
verbose whether or not to generate diagnostic output 
Method Summary
  model returns 
  test  
  train handle multiple datasets