prtOutlierRemovalMissingData  Removes missing data from a prtDataSet
 
    NSTDOUT = prtOutlierRemovalMissingData creates a pre-processing
    object that removes all missing data as outliers. Missing data are
    respresented as NaN's in the original data set.
 
    A prtOutlierRemovalMissingData object also inherits all properties and
    functions from the prtOutlierRemoval class.  For more information
    on how to control the behaviour of outlier removal objects, see the
    help for prtOutlierRemoval.
 
    Example:
 
    dataSet = prtDataGenUnimodal;               % Load a data Set
    outlier = prtDataSetClass([NaN NaN],1);     % Create and insert
    dataSet = catObservations(dataSet,outlier); % an Outlier
 
    % Create the prtOutlierRemoval object
    outRemove = prtOutlierRemovalMissingData('runMode','removeObservation');
 
    outRemove = outRemove.train(dataSet);    % Train and run
    dataSetNew = outRemove.run(dataSet);