Class encapsulating training data. More...

Public Member Functions
int	getCatCount (int vi)

Mat	getCatMap ()

Mat	getCatOfs ()

Mat	getClassLabels ()
	Returns the vector of class labels.

Mat	getDefaultSubstValues ()

int	getLayout ()

Mat	getMissing ()

int	getNAllVars ()

void	getNames (List< string > names)
	Returns vector of symbolic names captured in loadFromCSV()

IntPtr	getNativeObjAddr ()

Mat	getNormCatResponses ()

int	getNSamples ()

int	getNTestSamples ()

int	getNTrainSamples ()

int	getNVars ()

Mat	getResponses ()

int	getResponseType ()

void	getSample (Mat varIdx, int sidx, float buf)

Mat	getSamples ()

Mat	getSampleWeights ()

Mat	getTestNormCatResponses ()

Mat	getTestResponses ()

Mat	getTestSampleIdx ()

Mat	getTestSamples ()
	Returns matrix of test samples.

Mat	getTestSampleWeights ()

Mat	getTrainNormCatResponses ()
	Returns the vector of normalized categorical responses.

Mat	getTrainResponses ()
	Returns the vector of responses.

Mat	getTrainSampleIdx ()

Mat	getTrainSamples ()
	Returns matrix of train samples.

Mat	getTrainSamples (int layout)
	Returns matrix of train samples.

Mat	getTrainSamples (int layout, bool compressSamples)
	Returns matrix of train samples.

Mat	getTrainSamples (int layout, bool compressSamples, bool compressVars)
	Returns matrix of train samples.

Mat	getTrainSampleWeights ()

void	getValues (int vi, Mat sidx, float values)

Mat	getVarIdx ()

Mat	getVarSymbolFlags ()

Mat	getVarType ()

void	setTrainTestSplit (int count)
	Splits the training data into the training and test parts.

void	setTrainTestSplit (int count, bool shuffle)
	Splits the training data into the training and test parts.

void	setTrainTestSplitRatio (double ratio)
	Splits the training data into the training and test parts.

void	setTrainTestSplitRatio (double ratio, bool shuffle)
	Splits the training data into the training and test parts.

void	shuffleTrainTest ()

Public Member Functions inherited from OpenCVForUnity.DisposableObject
void	Dispose ()

void	ThrowIfDisposed ()

Static Public Member Functions
static TrainData	__fromPtr__ (IntPtr addr)

static TrainData	create (Mat samples, int layout, Mat responses)
	Creates training data from in-memory arrays.

static TrainData	create (Mat samples, int layout, Mat responses, Mat varIdx)
	Creates training data from in-memory arrays.

static TrainData	create (Mat samples, int layout, Mat responses, Mat varIdx, Mat sampleIdx)
	Creates training data from in-memory arrays.

static TrainData	create (Mat samples, int layout, Mat responses, Mat varIdx, Mat sampleIdx, Mat sampleWeights)
	Creates training data from in-memory arrays.

static TrainData	create (Mat samples, int layout, Mat responses, Mat varIdx, Mat sampleIdx, Mat sampleWeights, Mat varType)
	Creates training data from in-memory arrays.

static Mat	getSubMatrix (Mat matrix, Mat idx, int layout)
	Extract from matrix rows/cols specified by passed indexes.

static Mat	getSubVector (Mat vec, Mat idx)
	Extract from 1D vector elements specified by passed indexes.

Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr	ThrowIfNullIntPtr (IntPtr ptr)

Protected Member Functions
override void	Dispose (bool disposing)

Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
	DisposableOpenCVObject ()

	DisposableOpenCVObject (bool isEnabledDispose)

	DisposableOpenCVObject (IntPtr ptr)

	DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)

Protected Member Functions inherited from OpenCVForUnity.DisposableObject
	DisposableObject ()

	DisposableObject (bool isEnabledDispose)

Additional Inherited Members
Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject
Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed `[get, protected set]`

bool	IsEnabledDispose `[get, set]`

Detailed Description

Class encapsulating training data.

Please note that the class only specifies the interface of training data, but not implementation. All the statistical model classes in ml module accepts Ptr<TrainData> as parameter. In other words, you can create your own class derived from TrainData and pass smart pointer to the instance of this class into StatModel.train.

See also: ml_intro_data

Member Function Documentation

◆ fromPtr()

static TrainData OpenCVForUnity.MlModule.TrainData.__fromPtr__ ( IntPtr addr )

static