CreateNbcModel
Create a normal Bayes classifier of the specified type. The initial reference count is set to one if a new model is created and kept, otherwise. In order to train normal Bayes classifiers, a sufficiently high number of samples is required for each class. It depends on the number of features and the distribution of the data. Hence, it needs to be tested for each application. Models of this type do not support on-line training (sample by sample). For the retraining of such classifier models, the set of presented classes must be identical to the previous learning steps. Otherwise, an exception is raised.
Syntax
Definition:
HRESULT CreateNbcModel(
HRESULT hrPrev,
ITcVnMlModel*& ipMlModel,
ETcVnNbc eNbcType
)
Parameters
|
Name |
Type |
Description |
|---|---|---|
|
hrPrev |
HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.) | |
|
ipMlModel |
Returns the created model (Non-zero interface pointers are reused.) | |
|
eNbcType |
Normal Bayes classifier type |
Return valueRequired 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 |