MATLAB File Help: prtClassMap
 prtClassMap  Maximum a Posteriori classifier
     CLASSIFIER = prtClassMap returns a Maximum a Posteriori classifier
     CLASSIFIER = prtClassMap(PROPERTY1, VALUE1, ...) constructs a
     prtClassMAP object CLASSIFIER with properties as specified by
     PROPERTY/VALUE pairs.
     A prtClassMap object inherits all properties from the abstract class
     prtClass. In addition is has the following property:
     rvs    - A prtRv object. This property describes the random variable 
              model used for Maximum a Posteriori classification.
     A prtClassMap object inherits inherits the TRAIN, RUN, CROSSVALIDATE
     and KFOLDS methods from prtClass.
     TestDataSet = prtDataGenUnimodal;       % Create some test and
     TrainingDataSet = prtDataGenUnimodal;   % training data
     classifier = prtClassMap;               % Create a classifier
     classifier = classifier.train(TrainingDataSet);    % Train
     classified = run(classifier, TestDataSet);         % Test
     subplot(2,1,1); classifier.plot;  % Plot results
     subplot(2,1,2); prtScoreRoc(classified,TestDataSet);
     set(get(gca,'Children'), 'LineWidth',3)
See also
Class Details
Superclasses prtClass
Sealed false
Construct on load false
Constructor Summary
prtClassMap Maximum a Posteriori classifier 
Property Summary
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 True 
isSupervised True 
isTrained Indicates if prtAction object has been trained. 
name Required by prtAction 
nameAbbreviation MAP 
rvs Random variable object containing mean and variance 
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 the output confidence of a prtClass 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.