F_VN_CreateSvmModelExp

F_VN_CreateSvmModelExp 1:

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. (expert function)

Syntax

Definition:

FUNCTION F_VN_CreateSvmModelExp : HRESULT
VAR_INPUT
    ipMlModel      : Reference To ITcVnMlModel;
    eSvmType       : ETcVnSvm;
    fC             : LREAL;
    fNu            : LREAL;
    fP             : LREAL;
    eKernelType    : ETcVnSvmKernelType;
    fGamma         : LREAL;
    fCoef0         : LREAL;
    fDegree        : LREAL;
    nMaxIterations : UDINT;
    fEpsilon       : LREAL;
    hrPrev         : HRESULT;
END_VAR

F_VN_CreateSvmModelExp 2: Inputs

Name

Type

Description

ipMlModel

Reference To ITcVnMlModel

Returns the created model (Non-zero interface pointers are reused.)

eSvmType

ETcVnSvm

SVM model type

fC

LREAL

Parameter C (required for TCVN_SVM_C_CLASSIFIER, TCVN_SVM_EPS_REGRESSOR, and TCVN_SVM_NU_REGRESSOR; ignored otherwise)

fNu

LREAL

Parameter nu (required for TCVN_SVM_NU_CLASSIFIER, TCVN_SVM_NOVELTY_DETECTOR, and TCVN_SVM_NU_REGRESSOR; ignored otherwise)

fP

LREAL

Parameter p (required for TCVN_SVM_EPS_REGRESSOR; ignored otherwise)

eKernelType

ETcVnSvmKernelType

Kernel type

fGamma

LREAL

Parameter gamma (used by polynomial, RBF, sigmoid, and chi-squared kernels; ignored otherwise)

fCoef0

LREAL

Parameter coef0 (used by polynomial and sigmoid kernels; ignored otherwise)

fDegree

LREAL

Degree (used by polynomial kernels; ignored otherwise)

nMaxIterations

UDINT

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

LREAL

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)

hrPrev

HRESULT

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

F_VN_CreateSvmModelExp 3: Return value

HRESULT

Further information

The function F_VN_CreateSvmModelExp is an expert variant of F_VN_CreateSvmModel. It contains additional parameters.

Parameter

Model

The created model is returned in the interface pointer ipMlModel.

Model type

eSvmType specifies whether the SVM model is used for classification, regression or anomaly detection:

  • TCVN_SVM_C_CLASSIFIER
  • TCVN_SVM_NU_CLASSIFIER
  • TCVN_SVM_NOVELTY_DETECTOR
  • TCVN_SVM_EPS_REGRESSOR
  • TCVN_SVM_NU_REGRESSOR

Model parameters

The use and meaning of the parameters fC, fNu and fP depends on the selected eSvmType.

Kernel type

The kernel type used for the calculation is defined with eKernelType. The kernel type depends on the task / data distribution and must be adapted accordingly.

Kernel parameters

The use and meaning of the parameters fGamma, fCoef0 and fDegree depends on the selected eKernelType.

Maximum iterations

A maximum of as many iterations as specified in nMaxIterations are used for the optimization. If the value is 0, the respective default value is used.

Termination limit

The optimization is aborted as soon as the error between two iterations does not change more than specified in fEpsilon. If the value is 0, the respective default value is used.

Application

For example, an SVM model for classification can be created like this:

hr := F_VN_CreateSvmModelExp(
    ipMlModel       := ipMlModel,
    eSvmType        := TCVN_SVM_NU_CLASSIFIER,
    fC              := 0,
    fNu             := 0.1,
    fP              := 0,
    eKernelType     := TCVN_SKT_RBF,
    fGamma          := 1,
    fCoef0          := 0,
    fDegree         := 0,
    nMaxIterations  := 0,
    fEpsilon        := 0,
    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