F_VN_TrainSampleVector
Train a regressor with a single sample and vectorial output.
Syntax
Definition:
FUNCTION F_VN_TrainSampleVector : HRESULT
VAR_INPUT
ipRegressor : ITcVnMlModel;
ipSample : ITcUnknown;
ipOutput : ITcVnContainer;
hrPrev : HRESULT;
END_VAR
Inputs
|
Name |
Type |
Description |
|---|---|---|
|
ipRegressor |
Regressor to be used | |
|
ipSample |
Container holding a single input sample (ContainerType_Vector_REAL or ContainerType_Vector_LREAL) | |
|
ipOutput |
Vectorial output to be learnt (ContainerType_Vector_REAL or ContainerType_Vector_LREAL) | |
|
hrPrev |
HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.) |
Return valueFurther information
The function F_VN_TrainSampleVector trains a vector regressor model with a sample.
Parameter
Regressor model
The previously created regressor model must be transferred to ipRegressor.
Sample
The sample container is transferred as ipSample. The type of container must be ContainerType_Vector_REAL or ContainerType_Vector_LREAL.
Training vector
The result vector of the sample is transferred to ipOutput.
Application
For example, a vector regressor model can be trained with a single sample as follows:
hr := F_VN_TrainSampleVector(
ipRegressor:= ipRegressorModel,
ipSample := ipSample,
ipOutput := ipVector,
hrPrev := hr);
Related functions
Required License
TC3 Vision Machine Learning
System Requirements
Development environment | Target platform | PLC libraries to include |
|---|---|---|
TwinCAT V3.1.4024.54 or later | PC or CX (x64) with PL50, e.g. Intel 4-core Atom CPU | Tc3_Vision |