MATLAB File Help: prtClassLogisticDiscriminant
  prtClassLogisticDiscriminant  Logistic Discriminant classifier
     CLASSIFIER = prtClassLogisticDiscriminant returns a LogisticDiscriminant classifier
     CLASSIFIER = prtClassLogisticDiscriminant(PROPERTY1, VALUE1, ...) constructs a
     prtClassLogisticDiscriminant object CLASSIFIER with properties as specified by
     PROPERTY/VALUE pairs.
     A prtClassLogisticDiscriminant object inherits all properties from the abstract class
     prtClass. In addition is has the following properties:
    wTolerance       - The convergance tolerance of the weights
    irlsStepSize     - Step size used in training. Can be set to a
                       double, or 'hessian'. If 'hessian', IRLS is 
                       solved using the Hessian to estimate steps.
    maxIter          - maximum IRLS iterations
    nIterations      - number of iterations used, set during training
    wInitTechnique   - Technique to initialize weights, can be set to
                       'FLD', 'randn', and 'manual'
    manualInitialW   - The values the weights are initialized to if 
                       wInitTechnique is set to 'manual'
    wTolerance       - Convergence tolerance on weight vector 
    handleNonPosDefR - What to do when R is non-positive definte, can
                       be set to 'regularize' or 'exit'. When set to 
                       regularize, the classifier will attempt to
                       regularize the matrix. When set to exit the 
                       classifier will exit.
    w                - The regression weights, estimated during training
                       w(1) corresponds to the DC bias and w(2:end)
                       corresponds to the weights for the features
     For more information on LogisticDiscriminant classifiers, refer to the
     following URL:
     A prtClassLogisticDiscriminant 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 = prtClassLogisticDiscriminant;  % 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
prtClassLogisticDiscriminant Logistic Discriminant classifier 
Property Summary
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
handleNonPosDefR The action taken when R is non-positive definite 
internalDecider Optional prtDecider object for making decisions 
irlsStepSize The stepsize 
isCrossValidateValid True 
isNativeMary True 
isSupervised True 
isTrained Indicates if prtAction object has been trained. 
manualInitialW The value of the initial weights if initialized manually 
maxIter Maxmimuum number of iterations 
nIterations The number of iterations used in training 
name Logistic Discriminant 
nameAbbreviation LogDisc 
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 Regression weights 
wInitTechnique Weight initialization technique 
wTolerance The convergance tolerance of the weights 
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.