F_VN_TrainSampleVector

F_VN_TrainSampleVector 1:

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

F_VN_TrainSampleVector 2: Inputs

Name

Type

Description

ipRegressor

ITcVnMlModel

Regressor to be used

ipSample

ITcUnknown

Container holding a single input sample (ContainerType_Vector_REAL or ContainerType_Vector_LREAL)

ipOutput

ITcVnContainer

Vectorial output to be learnt (ContainerType_Vector_REAL or ContainerType_Vector_LREAL)

hrPrev

HRESULT

HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.)

F_VN_TrainSampleVector 3: Return value

HRESULT

Further 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(
    := ipRegressorModel,
    ipSample        := ipSample,
    ipOutput        := ipVector,
    hrPrev          := hr);

Related functions

Required License

TC3 Machine Learning Realtime Inference

System Requirements