MATLAB File Help: prtClassSvm
  prtClassSvm  Support vector machine classifier
     CLASSIFIER = prtClassSvm returns a support vector machine classifier
     CLASSIFIER = prtClassSvm(PROPERTY1, VALUE1, ...) constructs a
     prtClassSvm object CLASSIFIER with properties as specified by
     PROPERTY/VALUE pairs.
     A prtClassSvm object inherits all properties from the abstract class
     prtClass. In addition is has the following properties:
     c      - Slack variable weight 
     tol    - tolerance on learning updates 
     The following properties are read-only.
     alpha  - Vector of support vector machine weights
     beta   - Support vector machine DC offset
     For information on relevance vector machines, please
     refer to the following URL:
     The prtClassSvm object makes use of the sequential minimal
     optimization as described in Reference:
      J. Platt, Sequential Minimal Optimization: A Fast Algorithm
      for Training Support Vector Machines, Microsoft Research Technical
      Report MSR-TR-98-14, (1998).
     A prtClassSvm object inherits the TRAIN, RUN, CROSSVALIDATE and
     KFOLDS methods from prtAction. It also inherits the PLOT method
     from prtClass.
     TestDataSet = prtDataGenUnimodal;      % Create some test and
     TrainingDataSet = prtDataGenUnimodal;  % training data
     classifier = prtClassSvm;              % Create a classifier
     classifier = classifier.train(TrainingDataSet);    % Train
     classified = run(classifier, TestDataSet);         % Test
     [pf,pd] = prtScoreRoc(classified,TestDataSet);
     h = plot(pf,pd,'linewidth',3);
     title('ROC'); xlabel('Pf'); ylabel('Pd');
See also
Class Details
Superclasses prtClass
Sealed false
Construct on load false
Constructor Summary
prtClassSvm Support vector machine classifier 
Property Summary
alpha Vector of support vector machine weights 
beta Support vector machine DC offset 
c Slack parameter 
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
internalDecider Optional prtDecider object for making decisions 
isCrossValidateValid True 
isNativeMary False 
isSupervised True 
isTrained Indicates if prtAction object has been trained. 
kernels Kernels 
name Support Vector Machine 
nameAbbreviation SVM 
sparseKernels Trained kernels 
tol Tolerance 
twoClassParadigm Whether the classifier retures one output (binary) or two outputs (m-ary) when there are only two unique class labels 
userData User specified data 
verboseStorage Specifies whether or not to store the training prtDataset. 
Method Summary
  crossValidate Cross validate prtAction using prtDataSet and cross validation keys. 
  get get the object properties 
  kfolds Perform K-folds cross-validation of prtAction 
  optimize Optimize action parameter by exhaustive function maximization. 
  plot Plot output confidence of the prtClassSvm object 
  run Run a prtAction object on a prtDataSet object. 
  set set the object properties 
  train Train a prtAction object using training a prtDataSet object.