CVB.Net 15.0
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RegressionPredictorFactory Class Reference

Factory class for regression predictors. More...

Inherits PredictorFactoryBaseEx.

Public Member Functions

 RegressionPredictorFactory ()
 Ctor.
 
void UseSettingsFromPredictor (RegressionPredictor clf)
 Copy the predictor generation settings from a predictor.
 
void UseSettingsFromTestResult (RegressionTestResult res)
 Copy the predictor generation settings from a test result.
 
RegressionPredictor TrainPredictor (SampleRegressionImageList sil)
 Create a regression predictor from a sample image list.
 
- Public Member Functions inherited from PredictorFactoryBase
void Dispose ()
 Disposes of the native data needed for marshalling.
 
void UseSettingsFromPredictor (PredictorBase clf)
 Copy the classifier generation settings from a classifier.
 

Additional Inherited Members

- Static Public Member Functions inherited from PredictorFactoryBase
static string FormatPreprocessingCode (string input)
 Correct a preprocessing code to make sure that no invalid characters are in the code and the code does not exceed the maximum length.
 
- Static Public Attributes inherited from PredictorFactoryBaseEx
const InterpolationType InterpolationDefault = InterpolationType.Linear
 Default value for interpolation.
 
- Static Public Attributes inherited from PredictorFactoryBase
static readonly ValueRange< double > LambdaRange = new ValueRange<double>(0.0, 10.0)
 Acceptable scale factor range for search classifier training.
 
const double LambdaDefault = 0.1
 Default value for lambda.
 
const int FeatureResolutionDefault = 1
 Default value for feature resolution.
 
static readonly ValueRange< int > FeatureResolutionRange = new ValueRange<int>(0, 10)
 Valid range of feature resolution value.
 
const int PreprocessingMaxLength = InternalExtensions.PreprocessingMaxLength
 Maximum length of a preprocessing code (excluding the terminating zero).
 
const string PreprocessingValidCharacters = InternalExtensions.PreprocessingValidCharacters
 characters that a preprocessing string may contain.
 
- Protected Member Functions inherited from PredictorFactoryBase
 PredictorFactoryBase ()
 ctor (internal).
 
virtual void Dispose (bool disposing)
 Clean-up of managed-to-native data structures.
 
virtual void OnStartProgressReport (int id, string caption, int stepsTotal)
 Event raiser.
 
virtual void OnProgressReport (int id, ref bool retval)
 Event raiser.
 
virtual void OnEndProgressReport (int id)
 Event raiser.
 
- Properties inherited from PredictorFactoryBaseEx
InterpolationType Interpolation [get, set]
 Interpolation setting to be used for generating this object. Using interpolation will generate less artifacts, but requires more processor time.
 
int FeatureResolution [get, set]
 Feature resolution (determines the size of the classification retina.
 
- Properties inherited from PredictorFactoryBase
double Lambda [get, set]
 Regularization value to be used for generating the object. Possible values range from 0 to 10, good starting values for experiments are usually around 0.01.
 
string Preprocessing [get, set]
 Preprocessing code with which the object is to be generated.
 
- Events inherited from PredictorFactoryBase
EventHandler< StartProgressReportEventArgsStartProgressReport
 Event that will be fired when a new progress stage was initiated.
 
EventHandler< ProgressReportEventArgsProgressReport
 Event that informs about a progress step in the given stage.
 
EventHandler< EndProgressReportEventArgsEndProgressReport
 Event that informs about the finalization of a given stage.
 

Detailed Description

Factory class for regression predictors.

Member Function Documentation

◆ TrainPredictor()

Create a regression predictor from a sample image list.

Parameters
silSample image list to train from.
Returns
Newly generated classifier.
Exceptions
PolimagoFactoryExceptionTraining error (usually due to unsuitable parameters).

◆ UseSettingsFromPredictor()

void UseSettingsFromPredictor ( RegressionPredictor clf)

Copy the predictor generation settings from a predictor.

Parameters
clfClassifier to take the settings from.

◆ UseSettingsFromTestResult()

void UseSettingsFromTestResult ( RegressionTestResult res)

Copy the predictor generation settings from a test result.

Parameters
resTest result object from which to adopt the training settings.