CreatePcaTransformViaVariance
Create a PCA-based feature transform from the provided data based on a given fraction of variance to be retained. The maximum number of principal components that can be computed equals the minimum of the number of samples and the number of features. The initial reference count is set to one if a new model is created and kept, otherwise.
Syntax
Definition:
HRESULT CreatePcaTransformViaVariance(
HRESULT hrPrev,
ITcVnMlModel*& ipMlModel,
ITcUnknown* ipSamples,
double fRetainedVariance
)
Parameters
|
Name |
Type |
Description |
|---|---|---|
|
hrPrev |
HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.) | |
|
ipMlModel |
Returns the created feature transform (Non-zero interface pointers are reused.) | |
|
ipSamples |
Container holding a batch of input samples (ContainerType_Vector_Vector_REAL or ContainerType_Vector_Vector_LREAL) | |
|
fRetainedVariance |
double |
Fraction of variance that is to be retained by the PCA (A value of 1.0 signifies 100%.) |
Return valueRequired License
TC3 Vision Machine Learning
System Requirements
Development environment | Target platform | PLC libraries to include |
|---|---|---|
TwinCAT V3.1. 4024.44 or later | PC or CX (x64) with PL50, e.g. Intel 4-core Atom CPU | Tc3_Vision |