MATLAB File Help: prtPreProcZmuv
  prtPreProcZmuv   Zero mean unit variance processing
    ZMUV = prtPreProcZmuv creates a zero mean unit variance pre
    processing object. A prtPreProcZmuv object processes the input data
    so that it has zero mean and unit variance.  Use TRAIN to determine
    the parameters of the ZMUV object:
    zmuv = prtPreProcZmuv;
    zmuv = zmuv.train(ds); 
    And use RUN to process a data set:
    dsPreProc =;
    A prtPreProcZmuv object also inherits all properties and functions from
    the prtAction class
    dataSet = prtDataGenIris;       % Load a data set.
    dataSet = dataSet.retainFeatures(1:2);
    zmuv = prtPreProcZmuv;           % Create a zero-mean unit variance
                                     % object
    zmuv = zmuv.train(dataSet);      % Compute the mean and variance
    dataSetNew =;  % Normalize the data
    % Plot
    subplot(2,1,1); plot(dataSet);
    title(sprintf('Mean: %s; Stdev: %s',mat2str(mean(dataSet.getObservations),2),mat2str(std(dataSet.getObservations),2)))
    subplot(2,1,2); plot(dataSetNew);
    title(sprintf('Mean: %s; Stdev: %s',mat2str(mean(dataSetNew.getObservations),2),mat2str(std(dataSetNew.getObservations),2)))
See Also
Class Details
Superclasses prtPreProc
Sealed false
Construct on load false
Constructor Summary
prtPreProcZmuv Zero mean unit variance processing 
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 General Classifier Properties 
name Zero Mean Unit Variance 
nameAbbreviation ZMUV 
stds The original data standard deviation 
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.