CreateLbgModel

Create a LBG model of the specified type. The initial reference count is set to one if a new model is created and kept, otherwise. Models of this type neither support on-line training (sample by sample) nor retraining.

Syntax

Definition:

HRESULT CreateLbgModel(
    HRESULT                 hrPrev,
    ITcVnMlModel*&          ipMlModel,
    ETcVnPrototypeClusterer eLbgType,
    ULONG                   nMaxClusters,
    double                  fMaxClusterRadius,
    bool                    bSingleSplitSteps,
    bool                    bDoublePrecision = false,
    ULONG                   nMaxIterations = 0,
    double                  fEpsilon = 0.0
)

Parameters

Name	Type	Default	Description
hrPrev	HRESULT		HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.)
ipMlModel	ITcVnMlModel*&		Returns the created model (Non-zero interface pointers are reused.)
eLbgType	ETcVnPrototypeClusterer		LBG model type
nMaxClusters	ULONG		Maximum number of clusters
fMaxClusterRadius	double		Maximum allowed radius (L2 norm) of a single cluster, i.e. clusters with a higher radius will be split into smaller ones, until a global number of nMaxClusters is reached.
bSingleSplitSteps	bool		If true, the global optimization is always run after a single cluster has been split. If false, several clusters are split within the same step before applying the global optimization. Applying the global optimization less often is faster, but can lead to less optimal results, especially having 2 nearby clusters that could be represented by 1.
bDoublePrecision	bool	false	If true, the model is generated with double precision (LREAL) instead of single precision (REAL). (default: FALSE)
nMaxIterations	ULONG	0	Maximum number of iterations (triggers the usage of the default value of 10 if it equals 0)
fEpsilon	double	0.0	Maximum allowed difference of the error between two successive iterations (triggers the usage of the default value of 0.001 if it equals 0)

Return value

HRESULT

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