MATLAB File Help: prtClassAdaBoostFastAuc
 prtClassAdaBoostFastAuc AdaBoost classifier (fast training)
    prtClassAdaBoostFastAuc is a version of prtClassAdaBoost that can
    be trained significantly more quickly than prtClassAdaBoost.
    prtClassAdaBoostFastAuc acheives this by assuming a linear
    classifier when picking the feature to be used in the weak learner.
    Unlike regular adaBoost, where the weak learner is trained and
    evaluated on each feature, in prtClassAdaBoostFastAuc, the feature
    is selected using simple ROC metrics, and this feature is used to
    train the weak learner for the current iteration.  This can be
    significantly faster than prtClassAdaBoost when the base learner is
    slow, or there are a very large number of features.
    a = prtClassAdaBoostFastAuc;
    a = a.train(prtDataGenBimodal);
See also
Class Details
Superclasses prtClassAdaBoost
Sealed false
Construct on load false
Constructor Summary
prtClassAdaBoostFastAuc AdaBoost classifier (fast training) 
Property Summary
baseClassifier The weak classifier 
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. 
maxIters Max number of iterations 
name AdaBoost 
nameAbbreviation AdaBoost 
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. 
Static   fastRoc  
  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.