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Principal Component Analysis »
ApplyPCATransform
Applies previously obtained Principal Component Analysis (PCA) transformation coefficients to new data.
Syntax
C++
C#
void avl::ApplyPCATransform
(
const avl::Matrix& inMatrix,
const avl::PCAModel& inPCAModel,
avl::Matrix& outTransformedMatrix
)
void ApplyPCATransform
(
Matrix inMatrix,
PCAModel inPCAModel,
out Matrix outTransformedMatrix
)
Parameters
|
Name |
Type |
Default |
Description |
 |
inMatrix |
const Matrix& |
|
Input data with variables in columns and examples in rows. |
 |
inPCAModel |
const PCAModel& |
|
Previously created PCA model to apply to data provided in inMatrix. |
 |
outTransformedMatrix |
Matrix& |
|
Transformed inMatrix. |
Errors
| Error type |
Description |
| DomainError |
Malformed inPCAModel - MeanVector and StandardDeviationVector have to have the same length in ApplyPCATransform. |
| DomainError |
Malformed inPCAModel - MeanVector and StandardDeviationVector are not row-vectors in ApplyPCATransform. |
| DomainError |
PCAModel does not match - inMatrix column count does not match in ApplyPCATransform. |
| DomainError |
PCAModel does not match - StandardDeviationVector length is different then inMatrix column count in ApplyPCATransform. |
| DomainError |
PCAModel does not match - PCAFeatureVector dimensions does not correspond to inMatrix dimensions in ApplyPCATransform. |