MATLAB File Help: prtFeatSelExhaustive
  prtFeatSelExhaustive   Exhaustive feature selection
     FEATSEL = prtFeatSelExhaustive returns an exhaustive feature selection
     FEATSEL = prtFeatSelExhaustive(PROPERTY1, VALUE1, ...) constructs a
     prttFeatSelExhaustive object FEATSEL with properties as specified by
     A prtFeatSelExhaustive object has the following properties:
     nFeatures             - The number of features to be selected
     showProgressBar       - Flag indicating whether or not to show the
                             progress bar during feature selection.
     evaluationMetric      - The metric to be used to determine which
                             features are selected. evaluationMetric must
                             be a function handle. The function handle must
                             be in the form:
                             @(dataSet)prtEval(prtClass, dataSet, varargin)
                             where prtEval is a prtEval function, prtClass
                             is a prt classifier object, and varargin 
                             represents optional input arguments to a 
                             prtEval function.
     Peformance            - The performance obtained by the using the
                             features selected.
     selectedFeatures      - The indices of the features selected that gave
                             the best performance.
    A prtFeatSelExhaustive object inherits the TRAIN and RUN methods from prtClass.
    dataSet = prtDataGenFeatureSelection;      % Generate a data set
    featSel = prtFeatSelExhaustive;   % Create a feature selction object
    featSel.nFeatures = 3;            % Select only one feature of the data
    featSel = featSel.train(dataSet); % Train the feature selection object
    outDataSet =;% Extract the data set with only the
                                      % selected features
    %   Change the scoring function to prtScorePdAtPf, and change the
    %   classification method to prtClassMAP
    featSel.evaluationMetric = @(DS)prtEvalPdAtPf( prtClassMap, DS, .9);
    featSel = featSel.train(dataSet); 
    outDataSet =;
See Also
Class Details
Superclasses prtFeatSel
Sealed false
Construct on load false
Constructor Summary
prtFeatSelExhaustive Exhaustive feature selection 
Property Summary
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
evaluationMetric The metric used to evaluate performance 
isCrossValidateValid False 
isSupervised True 
isTrained Indicates if prtAction object has been trained. 
nFeatures The number of features to be selected 
name Exhaustive Feature Selection 
nameAbbreviation Efs 
performance The best performance of the selected feature set 
selectedFeatures The indices of the features selected  
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. 
  run Run a prtAction object on a prtDataSet object. 
  set set the object properties 
  train Train a prtAction object using training a prtDataSet object.