MATLAB File Help: prtClassFld
 prtClassFld Fisher linear discriminant classifier
     CLASSIFIER = prtClassFld returns a Fisher linear discriminant classifier
     CLASSIFIER = prtClassFld(PROPERTY1, VALUE1, ...) constructs a
     prtClassFld object CLASSIFIER with properties as specified by
     PROPERTY/VALUE pairs.
     A prtClassFld object inherits all properties from the abstract class
     prtClass. In addition is has the following properties:
     w                  - regression weights, estimated during training
     plotBasis          - Flag indicating whether to plot the basis
                          functions when the PLOT function is called
     plotProjections    - Flag indicating whether to plot the projection
                          of points to the basis when the PLOT function is
     For information on the Fisher Linear Discriminant algorithm, please
     refer to the following URL:
     A prtClassFld object inherits the TRAIN, RUN, CROSSVALIDATE and
     KFOLDS methods from prtAction. It also inherits the PLOT method from
     TestDataSet = prtDataGenUniModal;       % Create some test and
     TrainingDataSet = prtDataGenUniModal;   % training data
     classifier = prtClassFld;           % 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
prtClassFld Fisher linear discriminant 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 False 
isSupervised True 
isTrained Indicates if prtAction object has been trained. 
name Fisher Linear Discriminant 
nameAbbreviation FLD 
plotBasis plotting options 
plotProjections Flag indicating whether or not to plot the projections 
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. 
w The vector of weights, learned during training 
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.