Principal Components Analysis Transform
The PCA transform algorithm transforms the data set to principal components.
Details
Given a transformation matrix 
to the data set 
, 
.
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 to the data set Y
of size , .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 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  numeric table  .
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:
|
numeric table.
) numeric table, where the number of the columns is greater than or equal to 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  . If zero, the algorithm will compute the result for  . |
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  numeric table that contains data projected to the principal components basis.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 . |
Examples
C++ (CPU)
Batch Processing:
Java*
There is no support for Java on GPU.
Batch Processing:
Python* with DPC++ support
Batch Processing:
Python*
Batch Processing: