BasePrincipalComponentAnalysis Properties 
The BasePrincipalComponentAnalysis type exposes the following members.
Name  Description  

ComponentMatrix  Obsolete.
Gets a matrix whose columns contain the principal components. Also known as the Eigenvectors or loadings matrix.
 
ComponentProportions 
The respective role each component plays in the data set.
 
Components 
Gets the Principal Components in a objectoriented structure.
 
ComponentVectors 
Gets a matrix whose columns contain the principal components. Also known as the Eigenvectors or loadings matrix.
 
CumulativeProportions 
The cumulative distribution of the components proportion role. Also known
as the cumulative energy of the principal components.
 
Eigenvalues 
Provides access to the Eigenvalues stored during the analysis.
 
ExplainedVariance 
Gets or sets the amount of explained variance that should be generated
by this model. This value will alter the NumberOfOutputs
that can be generated by this model.
 
MaximumNumberOfOutputs 
Gets the maximum number of outputs (dimensionality of the output vectors)
that can be generated by this model.
 
Means 
Gets the column mean of the source data given at method construction.
 
Method 
Gets or sets the method used by this analysis.
 
NumberOfInputs 
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.)  
NumberOfOutputs 
Gets or sets the number of outputs (dimensionality of the output vectors)
that should be generated by this model.
 
Overwrite 
Gets or sets whether calculations will be performed overwriting
data in the original source matrix, using less memory.
 
Result  Obsolete.
Gets the resulting projection of the source
data given on the creation of the analysis
into the space spawned by principal components.
 
SingularValues 
Provides access to the Singular Values stored during the analysis.
If a covariance method is chosen, then it will contain an empty vector.
 
Source  Obsolete.
Returns the original data supplied to the analysis.
 
StandardDeviations 
Gets the column standard deviations of the source data given at method construction.
 
Token 
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
 
Whiten 
Gets or sets whether the transformation result should be whitened
(have unit standard deviation) before it is returned.
