CreateSvmModel

Create an SVM 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. Predictions can only be scalar. (additional expert function for C support vector classifiers)

Syntax

Definition:

HRESULT CreateSvmModel(
    HRESULT            hrPrev,
    ITcVnMlModel*&     ipMlModel,
    ETcVnSvm           eSvmType,
    double             fC,
    double             fNu,
    double             fP,
    ETcVnSvmKernelType eKernelType,
    double             fGamma,
    double             fCoef0,
    double             fDegree,
    ULONG              nMaxIterations = 0,
    double             fEpsilon = 0.0,
    ITcVnContainer*    ipClassWeights = nullptr
)

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.)
eSvmType	ETcVnSvm		SVM model type
fC	double		Parameter C (required for TCVN_SVM_C_CLASSIFIER, TCVN_SVM_EPS_REGRESSOR, and TCVN_SVM_NU_REGRESSOR; ignored otherwise)
fNu	double		Parameter nu (required for TCVN_SVM_NU_CLASSIFIER, TCVN_SVM_NOVELTY_DETECTOR, and TCVN_SVM_NU_REGRESSOR; ignored otherwise)
fP	double		Parameter p (required for TCVN_SVM_EPS_REGRESSOR; ignored otherwise)
eKernelType	ETcVnSvmKernelType		Kernel type
fGamma	double		Parameter gamma (used by polynomial, RBF, sigmoid, and chi-squared kernels; ignored otherwise)
fCoef0	double		Parameter coef0 (used by polynomial and sigmoid kernels; ignored otherwise)
fDegree	double		Degree (used by polynomial kernels; ignored otherwise)
nMaxIterations	ULONG	0	Maximum number of iterations (disabled if it equals 0 and fEpsilon is different from 0.0; triggers the usage of the default value of 100000 if nMaxIterations and fEpsilon equal 0)
fEpsilon	double	0.0	Maximum allowed difference of the error between two successive iterations (disabled if it equals 0.0 and nMaxIterations is different from 0; triggers the usage of the default value of 0.00001 if nMaxIterations and fEpsilon equal 0)
ipClassWeights	ITcVnContainer*	nullptr	Class weights (ContainerType_Vector_REAL or ContainerType_Vector_LREAL; only valid if eSvmType equals TCVN_SVM_C_CLASSIFIER; optional, set to 0 if not required or not allowed; default: 0)

Return value

HRESULT

Required 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