Intel® oneAPI Data Analytics Library Developer Guide and Reference
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Principal Components Analysis Transform
The PCA transform algorithm transforms the data set to principal components.
Details
Given a transformation matrix T computed by PCA (eigenvectors in row-major order) and data set X as input, the PCA Transform algorithm transforms input data set X of size \(n imes p\) to the data set Y of size \(n \times p_r\), \(pr \leq p\).
Batch Processing
Algorithm Input
The PCA Transform algorithm accepts the input described below. Pass the `Input ID` as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input ID |
Input |
|---|---|
data |
Use when the input data is a normalized or non-normalized data set. Pointer to the \(n imes p\) numeric table that contains the input data set. This input can be an object of any class derived from NumericTable. |
eigenvectors |
Principal components computed using the PCA algorithm. Pointer to the \(p_r \times p\) numeric table \((p_r \leq p)\). You can define it as an object of any class derived from NumericTable, except for PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable. |
dataForTransform |
Optional. Pointer to the key value-data collection containing the following data for PCA. The collection contains the following key-value pairs:
NOTE:
|
Algorithm Parameters
The PCA Transform algorithm has the following parameters:
Parameter |
method |
Default Value |
Description |
|---|---|---|---|
algorithmFPType |
defaultDense or svdDense |
float |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
nComponents |
defaultDense |
0 |
The number of principal components \((p_r \leq p)\). If zero, the algorithm will compute the result for \(\text{nComponents} = p_r\). |
Algorithm Output
The PCA Transform algorithm calculates the results described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm.
Result ID |
Result |
|---|---|
transformedData |
Pointer to the \(n \times p_r\) numeric table that contains data projected to the principal components basis.
NOTE:
By default, this result is an object of the HomogenNumericTable class, but you can define the result as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.
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Examples
C++ (CPU)
Batch Processing:
Java*
Batch Processing:
Python* with DPC++ support
Batch Processing:
Python*
Batch Processing: