MATLAB File Help: prtPreProcPca
  prtPreProcPca   Principle Component Analysis
    PCA = prtPreProcPca creates a Principle Component Analysis object.
    PCA = prtPreProcPca('nComponents',N) constructs a
    prtPreProcPCP object PCA with nComponents set to the value N.
    A prtPreProcPca object has the following properites:
    nComponents    - The number of principle componenets
    A prtPreProcPca object also inherits all properties and functions from
    the prtAction class
    dataSet = prtDataGenFeatureSelection;    % Load a data set
    pca = prtPreProcPca;            % Create a prtPreProcPca object
    pca = pca.train(dataSet);       % Train the prtPreProcPca object
    dataSetNew =;  % Run
    % Plot
    title('PCA Projected Data');
See Also
Class Details
Superclasses prtPreProc
Sealed false
Construct on load false
Constructor Summary
prtPreProcPca Principle Component Analysis 
Property Summary
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
isCrossValidateValid True 
isSupervised False 
isTrained Indicates if prtAction object has been trained. 
means A vector of the means 
nComponents The number of principle components 
name Principal Component Analysis 
nameAbbreviation PCA 
pcaVectors The PCA vectors. 
totalPercentVarianceCumulative reduced dimension data as a 
totalVariance training data 
totalVarianceCumulative dimension data. 
trainingTotalVariance The total variance contained in the 
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.