Functions
cvbbool_t	PMGetTestResultClassLabel (TTESTRESULT testResult, cvbval_t classIndex, char *szClassLabel)
	Get the class label corresponding to a given index and test result. More...

cvbbool_t	PMGetTestResultClassLabelW (TTESTRESULT testResult, cvbval_t classIndex, wchar_t *szClassLabel)
	Get the class label corresponding to a given index and test result. More...

double	PMGetTestResultConfidence (TTESTRESULT testResult, cvbval_t exampleIndex)
	Returns the confidence associated with the classification of a specified example. More...

double	PMGetTestResultConfidenceDistribution (TTESTRESULT testResult, cvbval_t exampleIndex, cvbval_t classIndex)
	Returns the confidence asserted by the classifier for a classification of a specified example to a specified class. More...

double	PMGetTestResultErrorRate (TTESTRESULT testResult)
	Returns the error rate (total number of errors divided by total number of examples) made during classification testing. More...

double	PMGetTestResultExampleMeanSquareError (TTESTRESULT testResult, cvbval_t ExampleIndex)
	Returns the mean square error on a test example over all output coordinates. More...

cvbval_t	PMGetTestResultNumClasses (TTESTRESULT testResult)
	Returns the number of classes for a classifier used in the test. More...

double	PMGetTestResultNumericalPrediction (TTESTRESULT testResult, cvbval_t exampleIndex, cvbval_t coordinateIndex)
	Returns the actual value predicted for a specified example and a specified output coordinate. More...

cvbval_t	PMGetTestResultNumErrors (TTESTRESULT testResult)
	Returns the total number of errors made during classification testing. More...

cvbval_t	PMGetTestResultNumExamples (TTESTRESULT testResult)
	Retrieves the number of examples that were tested. More...

cvbval_t	PMGetTestResultOutputDimension (TTESTRESULT testResult)
	Get the number of numerical values estimated for a given test result. More...

cvbval_t	PMGetTestResultPredictedClass (TTESTRESULT testResult, cvbval_t exampleIndex)
	Returns the class index which was predicted for a specific example. More...

double	PMGetTestResultTargetValue (TTESTRESULT testResult, cvbval_t exampleIndex, cvbval_t coordinateIndex)
	Returns the target value to be predicted for a specified example and a specified output coordinate. More...

double	PMGetTestResultTotalMeanSquareError (TTESTRESULT testResult)
	Returns the mean square error of the predictor over all examples and all coordinates. More...

void	PMGetTestResultTrainParams (TTESTRESULT testResult, TTrainParams &params)
	Retrieves the training parameters that were used for generating a test result. More...

cvbval_t	PMGetTestResultTrueClassIndex (TTESTRESULT testResult, cvbval_t exampleIndex)
	Returns the index of the true class to which an example belongs. More...

TPolimagoTrainingError	PMLeaveOutTestGeneric (TLEARNINGDATAACCESS db, TProgress Progress, cvbval_t HoldOutSize, TClassifierUsage usage, const char szPreproCode, cvbval_t featureResolution, double lambda, cvbbool_t interpolate, TTESTRESULT &TestResult)
	Performs a leave-out-crossvalidation on the specified training data set. More...

TPolimagoTrainingError	PMLeaveOutTestOnMts (MTS mts, TProgress Progress, cvbval_t HoldOutSize, TClassifierUsage usage, const char szPreproCode, cvbval_t featureResolution, double lambda, cvbbool_t interpolate, TTESTRESULT &TestResult)
	Performs a leave-out-crossvalidation on the specified training data set. More...

TPolimagoTrainingError	PMLeaveOutTestOnSil (TSIL sil, TProgress Progress, cvbval_t HoldOutSize, TClassifierUsage usage, const char szPreproCode, cvbval_t featureResolution, double lambda, cvbbool_t interpolate, TTESTRESULT &TestResult)
	Performs a leave-out-crossvalidation on the specified training data set. More...

cvbbool_t	PMOpenTestResult (const char *szFileName, TTESTRESULT &testResult)
	Loads the result of a sample test or a leave out test from a file. More...

cvbbool_t	PMOpenTestResultW (const wchar_t *szFileName, TTESTRESULT &testResult)
	Loads the result of a sample test or a leave out test from a file. More...

TPolimagoTrainingError	PMSampleTestGeneric (TLEARNINGDATAACCESS db, TProgress *Progress, TCLF Clf, TTESTRESULT &TestResult)
	Test a given classifier on test data available as generic data access. More...

TPolimagoTrainingError	PMSampleTestOnMts (MTS mts, TProgress *Progress, TCLF Clf, TTESTRESULT &TestResult)
	Test a given classifier on test data available as a MTS (Minos Training Set). More...

TPolimagoTrainingError	PMSampleTestOnSil (TSIL sil, TProgress *Progress, TCLF Clf, TTESTRESULT &TestResult)
	Test a given classifier on test data available as a SIL (Sample Image List). More...

cvbbool_t	PMSaveTestResult (const char *szFileName, TTESTRESULT testResult)
	Save the result of a sample test or a leave out test to a file. More...

cvbbool_t	PMSaveTestResultW (const wchar_t *szFileName, TTESTRESULT testResult)
	Save the result of a sample test or a leave out test to a file. More...

Detailed Description

Function Documentation

◆ PMGetTestResultClassLabel()

cvbbool_t PMGetTestResultClassLabel	(	TTESTRESULT	testResult,
		cvbval_t	classIndex,
		char *	szClassLabel
	)

Get the class label corresponding to a given index and test result.

Attention: The buffer pointed to by szClassLabel must be big enough to hold the entire class label, otherwise a write access violation may occur. To be on the safe side, alway allocate at least 256 bytes.

Parameters

[in]	testResult	Handle of the test result container.
[in]	classIndex	Index of the class in question. Must be nonnegative and smaller than the return value of PMGetTestResultNumClasses.
[in]	szClassLabel	Pointer to a buffer that will receive the class label string (zero-terminated!.

Returns: TRUE if the call was successful (i.e. all parameters are valid) FALSE otherwise.

◆ PMGetTestResultClassLabelW()

cvbbool_t PMGetTestResultClassLabelW	(	TTESTRESULT	testResult,
		cvbval_t	classIndex,
		wchar_t *	szClassLabel
	)

Get the class label corresponding to a given index and test result.

Attention: The buffer pointed to by szClassLabel must be big enough to hold the entire class label, otherwise a write access violation may occur. To be on the safe side, alway allocate at least 256 bytes.

Parameters

[in]	testResult	Handle of the test result container.
[in]	classIndex	Index of the class in question. Must be nonnegative and smaller than the return value of PMGetTestResultNumClasses.
[in]	szClassLabel	Pointer to a buffer that will receive the class label string (zero-terminated!.

Returns: TRUE if the call was successful (i.e. all parameters are valid) FALSE otherwise.

◆ PMGetTestResultConfidence()

double PMGetTestResultConfidence	(	TTESTRESULT	testResult,
		cvbval_t	exampleIndex
	)

Returns the confidence associated with the classification of a specified example.

Parameters

[in]	testResult	Handle of the test result container.
[in]	exampleIndex	Index of example.

Returns: Confidence in classification for the example.

◆ PMGetTestResultConfidenceDistribution()

double PMGetTestResultConfidenceDistribution	(	TTESTRESULT	testResult,
		cvbval_t	exampleIndex,
		cvbval_t	classIndex
	)

Returns the confidence asserted by the classifier for a classification of a specified example to a specified class.

Parameters

[in]	testResult	Handle of the test result container.
[in]	exampleIndex	Index of example.
[in]	classIndex	Index of class.

Returns: Relative confidence.

◆ PMGetTestResultErrorRate()

double PMGetTestResultErrorRate ( TTESTRESULT testResult )

Returns the error rate (total number of errors divided by total number of examples) made during classification testing.

Parameters

[in] testResult Handle of the test result container.

Returns: Error rate of the test result.

◆ PMGetTestResultExampleMeanSquareError()

double PMGetTestResultExampleMeanSquareError	(	TTESTRESULT	testResult,
		cvbval_t	ExampleIndex
	)

Returns the mean square error on a test example over all output coordinates.

Parameters

[in]	testResult	Handle of the test result container.
[in]	ExampleIndex	Index of an example in the test result.

Returns: Mean square error for the queried example.

◆ PMGetTestResultNumClasses()

cvbval_t PMGetTestResultNumClasses ( TTESTRESULT testResult )

Returns the number of classes for a classifier used in the test.

For tests calculated with usage = CU_Regression the return value will be zero.

Parameters

[in] testResult Handle of the test result container.

Returns: Number of classes involved in the test.

◆ PMGetTestResultNumericalPrediction()

double PMGetTestResultNumericalPrediction	(	TTESTRESULT	testResult,
		cvbval_t	exampleIndex,
		cvbval_t	coordinateIndex
	)

Returns the actual value predicted for a specified example and a specified output coordinate.

Parameters

[in]	testResult	Handle of the test result container.
[in]	exampleIndex	Index of test example.
[in]	coordinateIndex	Coordinate index of predictor output. Must be larger or equal to zero and less than the result of PMGetTestResultOutputDimension.

Returns: Predicted sample value (compare to output of PMGetTestResultTargetValue to verify correctness).

◆ PMGetTestResultNumErrors()

cvbval_t PMGetTestResultNumErrors ( TTESTRESULT testResult )

Returns the total number of errors made during classification testing.

Parameters

[in] testResult Handle of the test result container.

Returns: Number of errors in the test result.

◆ PMGetTestResultNumExamples()

cvbval_t PMGetTestResultNumExamples ( TTESTRESULT testResult )

Retrieves the number of examples that were tested.

Parameters

[in] testResult Handle of the test result container.

Returns: The number of examples.

◆ PMGetTestResultOutputDimension()

cvbval_t PMGetTestResultOutputDimension ( TTESTRESULT testResult )

Get the number of numerical values estimated for a given test result.

For tests based on numerical regression (usage = CU_Regression) the result will match the label dimension used in the training database. For tests with usage = CU_ClassifyOneVersusAll the output dimension will equal the number of classes in the training database. For usage = CU_ClassifyOneVersusOne the output dimension is

(numclasses-1) * numclasses / 2

.

Parameters

[in] testResult Handle of the test result container.

Returns: The number of numerical values estimated in each step.

◆ PMGetTestResultPredictedClass()

cvbval_t PMGetTestResultPredictedClass	(	TTESTRESULT	testResult,
		cvbval_t	exampleIndex
	)

Returns the class index which was predicted for a specific example.

Parameters

[in]	testResult	Handle of the test result container.
[in]	exampleIndex	Index of example.

Returns: Predicted class index of the example.

◆ PMGetTestResultTargetValue()

double PMGetTestResultTargetValue	(	TTESTRESULT	testResult,
		cvbval_t	exampleIndex,
		cvbval_t	coordinateIndex
	)

Returns the target value to be predicted for a specified example and a specified output coordinate.

Parameters

[in]	testResult	Handle of the test result container.
[in]	exampleIndex	Index of test example.
[in]	coordinateIndex	Coordinate index of predictor output. Must be larger or equal to zero and less than the result of PMGetTestResultOutputDimension.

Returns: Theoretically correct result of the prediction.

◆ PMGetTestResultTotalMeanSquareError()

double PMGetTestResultTotalMeanSquareError ( TTESTRESULT testResult )

Returns the mean square error of the predictor over all examples and all coordinates.

Parameters

[in] testResult Handle of the test result container.

Returns: The total mean square error.

◆ PMGetTestResultTrainParams()

void PMGetTestResultTrainParams	(	TTESTRESULT	testResult,
		TTrainParams &	params
	)

Retrieves the training parameters that were used for generating a test result.

Parameters

[in]	testResult	Handle of the test result container.
[out]	params	The training parameters used during generation of the test result.

◆ PMGetTestResultTrueClassIndex()

cvbval_t PMGetTestResultTrueClassIndex	(	TTESTRESULT	testResult,
		cvbval_t	exampleIndex
	)

Returns the index of the true class to which an example belongs.

Parameters

[in]	testResult	Handle of the test result container.
[in]	exampleIndex	Index of example.

Returns: True class index of the example.

◆ PMLeaveOutTestGeneric()

TPolimagoTrainingError PMLeaveOutTestGeneric	(	TLEARNINGDATAACCESS	db,
		TProgress *	Progress,
		cvbval_t	HoldOutSize,
		TClassifierUsage	usage,
		const char *	szPreproCode,
		cvbval_t	featureResolution,
		double	lambda,
		cvbbool_t	interpolate,
		TTESTRESULT &	TestResult
	)

Performs a leave-out-crossvalidation on the specified training data set.

In a leave-out-crossvalidation a number of training examples (holdout set) is removed from the data training set each on each step and is used for testing with a classifier that is generated from the rest of the training samples. The process is repeated until every example in the whole data set has been tested once.

Parameters

[in]	db	Handle of the training data set as returned by PMCreateLearningDataAccess. Note that the set of callbacks specified in the call to PMCreateLearningDataAccess must match the value of the usage mode parameter!
[in]	Progress	Callback structure for progress report. May be used to show testing progress on the user interface (see description of TProgress).
[in]	HoldOutSize	Number of examples to leave out on each pass.
[in]	usage	Classifier usage (see description of TClassifierUsage).
[in]	szPreproCode	Preprocessing code to be used for the training steps of the test.
[in]	featureResolution	Determines the dimensions of the classifier's retina (see feature-map lesson in the tutorial on search functions)
[in]	lambda	Ridge regression regularization constant. The default value 0.01 works well in most cases. May be slightly increased for very small numbers of training examples and slightly decreased for very large numbers of training examples.
[in]	interpolate	Image interpolation mode for feature extraction. `implies` simple truncation of fractional coordinates, `TRUE` (recommended) implies bilinear interpolation.
[out]	TestResult	Receives the handle to the test result container (see description of TTESTRESULT).

Returns: One of the return codes defined in TPolimagoTrainingError.

◆ PMLeaveOutTestOnMts()

TPolimagoTrainingError PMLeaveOutTestOnMts	(	MTS	mts,
		TProgress *	Progress,
		cvbval_t	HoldOutSize,
		TClassifierUsage	usage,
		const char *	szPreproCode,
		cvbval_t	featureResolution,
		double	lambda,
		cvbbool_t	interpolate,
		TTESTRESULT &	TestResult
	)

Performs a leave-out-crossvalidation on the specified training data set.

In a leave-out-crossvalidation a number of training examples (holdout set) is removed from the data training set each on each step and is used for testing with a classifier that is generated from the rest of the training samples. The process is repeated until every example in the whole data set has been tested once.

Parameters

[in]	mts	Specifies the training data set.
[in]	Progress	Callback structure for progress report. May be used to show testing progress on the user interface (see description of TProgress).
[in]	HoldOutSize	Number of examples to leave out on each pass.
[in]	usage	Classifier usage (see description of TClassifierUsage).
[in]	szPreproCode	Preprocessing code to be used for the training steps of the test.
[in]	featureResolution	Determines the dimensions of the classifier's retina (see feature-map lesson in the tutorial on search functions)
[in]	lambda	Ridge regression regularization constant. The default value 0.01 works well in most cases. May be slightly increased for very small numbers of training examples and slightly decreased for very large numbers of training examples.
[in]	interpolate	Image interpolation mode for feature extraction. `implies` simple truncation of fractional coordinates, `TRUE` (recommended) implies bilinear interpolation.
[out]	TestResult	Receives the handle to the test result container (see description of TTESTRESULT).

Returns: One of the return codes defined in TPolimagoTrainingError.

◆ PMLeaveOutTestOnSil()

TPolimagoTrainingError PMLeaveOutTestOnSil	(	TSIL	sil,
		TProgress *	Progress,
		cvbval_t	HoldOutSize,
		TClassifierUsage	usage,
		const char *	szPreproCode,
		cvbval_t	featureResolution,
		double	lambda,
		cvbbool_t	interpolate,
		TTESTRESULT &	TestResult
	)

Performs a leave-out-crossvalidation on the specified training data set.

In a leave-out-crossvalidation a number of training examples (holdout set) is removed from the data training set each on each step and is used for testing with a classifier that is generated from the rest of the training samples. The process is repeated until every example in the whole data set has been tested once.

Parameters

[in]	sil	Specifies the training data set.
[in]	Progress	Callback structure for progress report. May be used to show testing progress on the user interface (see description of TProgress).
[in]	HoldOutSize	Number of examples to leave out on each pass.
[in]	usage	Classifier usage (see description of TClassifierUsage).
[in]	szPreproCode	Preprocessing code to be used for the training steps of the test.
[in]	featureResolution	Determines the dimensions of the classifier's retina (see feature-map lesson in the tutorial on search functions)
[in]	lambda	Ridge regression regularization constant. The default value 0.01 works well in most cases. May be slightly increased for very small numbers of training examples and slightly decreased for very large numbers of training examples.
[in]	interpolate	Image interpolation mode for feature extraction. `implies` simple truncation of fractional coordinates, `TRUE` (recommended) implies bilinear interpolation.
[out]	TestResult	Receives the handle to the test result container (see description of TTESTRESULT).

Returns: One of the return codes defined in TPolimagoTrainingError.

◆ PMOpenTestResult()

cvbbool_t PMOpenTestResult	(	const char *	szFileName,
		TTESTRESULT &	testResult
	)

Loads the result of a sample test or a leave out test from a file.

If the test result can be successfully loaded from the given path its reference count will be initialized to 1 and a ReleaseObject call (see CVCImg.dll reference) will be needed to release the memory occupied by the classifier.

Parameters

[in]	szFileName	Pointer to a zero-terminated string containing the name of the file to be loaded.
[out]	testResult	Receives the test result handle if the test result was loaded successfully.

Returns: TRUE if loading the test result from the specified path was successful, FALSE if not

◆ PMOpenTestResultW()

cvbbool_t PMOpenTestResultW	(	const wchar_t *	szFileName,
		TTESTRESULT &	testResult
	)

Loads the result of a sample test or a leave out test from a file.

If the test result can be successfully loaded from the given path its reference count will be initialized to 1 and a ReleaseObject call (see CVCImg.dll reference) will be needed to release the memory occupied by the classifier.

Parameters

[in]	szFileName	Pointer to a zero-terminated string containing the name of the file to be loaded.
[out]	testResult	Receives the test result handle if the test result was loaded successfully.

Returns: TRUE if loading the test result from the specified path was successful, FALSE if not

◆ PMSampleTestGeneric()

TPolimagoTrainingError PMSampleTestGeneric	(	TLEARNINGDATAACCESS	db,
		TProgress *	Progress,
		TCLF	Clf,
		TTESTRESULT &	TestResult
	)

Test a given classifier on test data available as generic data access.

Performs a sample test of a classifier on a set of learning data, i.e. every single example inside the learning set is classified using the classifier Clf and the result is compared versus the sample's true label.

Parameters

[in]	db	Handle of the training data set as returned by PMCreateLearningDataAccess. Note that the set of callbacks specified in the call to PMCreateLearningDataAccess must match the classifier's usage mode!
[in]	Progress	Callback structure for progress report. Can be used to show training progress on the user interface (see description of the TProgress struct).
[in]	Clf	Handle of the classifier to be used for testing.
[out]	TestResult	Receives the handle of the aggregated test result (see description of TTESTRESULT).

Returns: One of the return codes defined in TPolimagoTrainingError.

◆ PMSampleTestOnMts()

TPolimagoTrainingError PMSampleTestOnMts	(	MTS	mts,
		TProgress *	Progress,
		TCLF	Clf,
		TTESTRESULT &	TestResult
	)

Test a given classifier on test data available as a MTS (Minos Training Set).

Performs a sample test of a classifier on a minos training set, i.e. every single sample inside the training set is classified using the classifier Clf and the result is compared versus the sample's true label.

Parameters

[in]	mts	Handle of the training data set.
[in]	Progress	Callback structure for progress report. Can be used to show training progress on the user interface (see description of the TProgress struct).
[in]	Clf	Handle of the classifier to be used for testing.
[out]	TestResult	Receives the handle of the aggregated test result (see description of TTESTRESULT).

Returns: One of the return codes defined in TPolimagoTrainingError.

◆ PMSampleTestOnSil()

TPolimagoTrainingError PMSampleTestOnSil	(	TSIL	sil,
		TProgress *	Progress,
		TCLF	Clf,
		TTESTRESULT &	TestResult
	)

Test a given classifier on test data available as a SIL (Sample Image List).

Performs a sample test of a classifier on a sample image list, i.e. every single sample inside the sample image list is classified using the classifier Clf and the result is compared versus the sample's true label.

Parameters

[in]	sil	Handle of the training data set.
[in]	Progress	Callback structure for progress report. Can be used to show training progress on the user interface (see description of the TProgress struct).
[in]	Clf	Handle of the classifier to be used for testing.
[out]	TestResult	Receives the handle of the aggregated test result (see description of TTESTRESULT).

Returns: One of the return codes defined in TPolimagoTrainingError.

◆ PMSaveTestResult()

cvbbool_t PMSaveTestResult	(	const char *	szFileName,
		TTESTRESULT	testResult
	)

Save the result of a sample test or a leave out test to a file.

Parameters

[in]	szFileName	Pointer to the zero-terminated string containing the file name to save the test result to. Note that existing files will be overwritten.
[in]	testResult	Handle of the test result.

Returns: TRUE if saving the classifier to the specified path was successful, FALSE if not

◆ PMSaveTestResultW()

cvbbool_t PMSaveTestResultW	(	const wchar_t *	szFileName,
		TTESTRESULT	testResult
	)

Save the result of a sample test or a leave out test to a file.

Parameters

[in]	szFileName	Pointer to the zero-terminated string containing the file name to save the test result to. Note that existing files will be overwritten.
[in]	testResult	Handle of the test result.

Returns: TRUE if saving the classifier to the specified path was successful, FALSE if not

Functions

Detailed Description

Function Documentation

◆ PMGetTestResultClassLabel()

◆ PMGetTestResultClassLabelW()

◆ PMGetTestResultConfidence()

◆ PMGetTestResultConfidenceDistribution()

◆ PMGetTestResultErrorRate()

◆ PMGetTestResultExampleMeanSquareError()

◆ PMGetTestResultNumClasses()

◆ PMGetTestResultNumericalPrediction()

◆ PMGetTestResultNumErrors()

◆ PMGetTestResultNumExamples()

◆ PMGetTestResultOutputDimension()

◆ PMGetTestResultPredictedClass()

◆ PMGetTestResultTargetValue()

◆ PMGetTestResultTotalMeanSquareError()

◆ PMGetTestResultTrainParams()

◆ PMGetTestResultTrueClassIndex()

◆ PMLeaveOutTestGeneric()

◆ PMLeaveOutTestOnMts()

◆ PMLeaveOutTestOnSil()

◆ PMOpenTestResult()

◆ PMOpenTestResultW()

◆ PMSampleTestGeneric()

◆ PMSampleTestOnMts()

◆ PMSampleTestOnSil()

◆ PMSaveTestResult()

◆ PMSaveTestResultW()