Principal Components Analysis Transform¶
The PCA transform algorithm transforms the data set to principal components.
Details¶
Given a transformation matrix
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 |
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|
Use when the input data is a normalized or non-normalized data set. Pointer to the |
|
Principal components computed using the PCA algorithm. Pointer to the |
|
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 |
---|---|---|---|
|
|
|
The floating-point type that the algorithm uses for intermediate computations. Can be |
|
|
The number of principal components |
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 |
---|---|
|
Pointer to the Note By default, this result is an object of the |
Examples¶
Batch Processing: