F_VN_CreateBoostClassifier

Create a Boost classifier using the default parameters. The initial reference count is set to one if a new model is created and kept, otherwise. The Boost classifier is only applicable to binary classification problems. It learns to distinguish between samples labelled with two user-defined class labels by incrementally adding weak classifiers to improve the classification results. Models of this type neither support on-line training (sample by sample) nor retraining.

Syntax

Definition:

FUNCTION F_VN_CreateBoostClassifier : HRESULT
VAR_INPUT
    ipMlModel : Reference To  ITcVnMlModel;
    hrPrev    : HRESULT;
END_VAR

Inputs

Name	Type	Description
ipMlModel	Reference To ITcVnMlModel	Returns the created model (Non-zero interface pointers are reused.)
hrPrev	HRESULT	HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.)

Return value

HRESULT

Further information

The function F_VN_CreateBoostClassifier creates a boost classifier model.

Boost classifier models

The boost classifier model is only suitable for binary classification problems. This model learns to distinguish between samples labeled with two user-defined class labels by incrementally adding weak classifiers to improve classification results.

Parameter

Model

The created model is returned in the interface pointer ipMlModel.

Expert parameters

The expert variants F_VN_CreateBoostClassifierExp and F_VN_CreateBoostClassifierExp2 contain additional parameters.

Application

A boost classifier model can be created like this, for example:

hr := F_VN_CreateBoostClassifier(
    ipMlModel   := ipMlModel,
    hrPrev      := hr);

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