The class implements the random forest predictor. More...

Inheritance diagram for OpenCVForUnity.MlModule.RTrees:

Public Member Functions
bool	getCalculateVarImportance ()

void	setCalculateVarImportance (bool val)

int	getActiveVarCount ()

void	setActiveVarCount (int val)

TermCriteria	getTermCriteria ()

void	setTermCriteria (TermCriteria val)

Mat	getVarImportance ()

void	getVotes (Mat samples, Mat results, int flags)

double	getOOBError ()

Public Member Functions inherited from OpenCVForUnity.MlModule.DTrees
int	getMaxCategories ()

void	setMaxCategories (int val)

int	getMaxDepth ()

void	setMaxDepth (int val)

int	getMinSampleCount ()

void	setMinSampleCount (int val)

int	getCVFolds ()

void	setCVFolds (int val)

bool	getUseSurrogates ()

void	setUseSurrogates (bool val)

bool	getUse1SERule ()

void	setUse1SERule (bool val)

bool	getTruncatePrunedTree ()

void	setTruncatePrunedTree (bool val)

float	getRegressionAccuracy ()

void	setRegressionAccuracy (float val)

Mat	getPriors ()

void	setPriors (Mat val)

Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel
int	getVarCount ()
	Returns the number of variables in training samples. More...

override bool	empty ()
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...

bool	isTrained ()
	Returns true if the model is trained. More...

bool	isClassifier ()
	Returns true if the model is classifier. More...

bool	train (TrainData trainData, int flags)
	Trains the statistical model. More...

bool	train (TrainData trainData)
	Trains the statistical model. More...

bool	train (Mat samples, int layout, Mat responses)
	Trains the statistical model. More...

float	calcError (TrainData data, bool test, Mat resp)
	Computes error on the training or test dataset. More...

virtual float	predict (Mat samples, Mat results, int flags)
	Predicts response(s) for the provided sample(s) More...

virtual float	predict (Mat samples, Mat results)
	Predicts response(s) for the provided sample(s) More...

virtual float	predict (Mat samples)
	Predicts response(s) for the provided sample(s) More...

Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
IntPtr	getNativeObjAddr ()

virtual void	clear ()
	Clears the algorithm state. More...

void	save (string filename)

virtual string	getDefaultName ()

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

void	ThrowIfDisposed ()

Static Public Member Functions
static new RTrees	__fromPtr__ (IntPtr addr)

static new RTrees	create ()

static new RTrees	load (string filepath, string nodeName)
	Loads and creates a serialized RTree from a file. More...

static new RTrees	load (string filepath)
	Loads and creates a serialized RTree from a file. More...

Static Public Member Functions inherited from OpenCVForUnity.MlModule.DTrees
static new DTrees	__fromPtr__ (IntPtr addr)

static DTrees	create ()
	Creates the empty model. More...

static DTrees	load (string filepath, string nodeName)
	Loads and creates a serialized DTrees from a file. More...

static DTrees	load (string filepath)
	Loads and creates a serialized DTrees from a file. More...

Static Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel
static new StatModel	__fromPtr__ (IntPtr addr)

Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
static Algorithm	__fromPtr__ (IntPtr addr)

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.MlModule.StatModel
override void	Dispose (bool disposing)

Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
	DisposableOpenCVObject ()

	DisposableOpenCVObject (IntPtr ptr)

	DisposableOpenCVObject (bool isEnabledDispose)

	DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)

Protected Member Functions inherited from OpenCVForUnity.DisposableObject
	DisposableObject ()

	DisposableObject (bool isEnabledDispose)

Additional Inherited Members
Public Attributes inherited from OpenCVForUnity.MlModule.DTrees
const int	PREDICT_AUTO = 0

const int	PREDICT_SUM = (1 << 8)

const int	PREDICT_MAX_VOTE = (2 << 8)

const int	PREDICT_MASK = (3 << 8)

Public Attributes inherited from OpenCVForUnity.MlModule.StatModel
const int	UPDATE_MODEL = 1

const int	RAW_OUTPUT = 1

const int	COMPRESSED_INPUT = 2

const int	PREPROCESSED_INPUT = 4

Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed `[get, protected set]`

bool	IsEnabledDispose `[get, set]`

Detailed Description

The class implements the random forest predictor.

See also: ml_intro_rtrees

Member Function Documentation

◆ fromPtr()

static new RTrees OpenCVForUnity.MlModule.RTrees.__fromPtr__ ( IntPtr addr )

static

◆ create()

static new RTrees OpenCVForUnity.MlModule.RTrees.create ( )

static

Creates the empty model. Use StatModel::train to train the model, StatModel::train to create and train the model, Algorithm::load to load the pre-trained model.

◆ Dispose()

override void OpenCVForUnity.MlModule.RTrees.Dispose ( bool disposing )

protectedvirtual

Reimplemented from OpenCVForUnity.MlModule.DTrees.

◆ getActiveVarCount()

int OpenCVForUnity.MlModule.RTrees.getActiveVarCount ( )

See also: setActiveVarCount

◆ getCalculateVarImportance()

bool OpenCVForUnity.MlModule.RTrees.getCalculateVarImportance ( )

See also: setCalculateVarImportance

◆ getOOBError()

double OpenCVForUnity.MlModule.RTrees.getOOBError ( )

Returns the OOB error value, computed at the training stage when calcOOBError is set to true. If this flag was set to false, 0 is returned. The OOB error is also scaled by sample weighting.

◆ getTermCriteria()

TermCriteria OpenCVForUnity.MlModule.RTrees.getTermCriteria ( )

See also: setTermCriteria

◆ getVarImportance()

Mat OpenCVForUnity.MlModule.RTrees.getVarImportance ( )

Returns the variable importance array. The method returns the variable importance vector, computed at the training stage when CalculateVarImportance is set to true. If this flag was set to false, the empty matrix is returned.

◆ getVotes()

void OpenCVForUnity.MlModule.RTrees.getVotes	(	Mat	samples,
		Mat	results,
		int	flags
	)

Returns the result of each individual tree in the forest. In case the model is a regression problem, the method will return each of the trees' results for each of the sample cases. If the model is a classifier, it will return a Mat with samples + 1 rows, where the first row gives the class number and the following rows return the votes each class had for each sample.

Parameters

samples	Array containing the samples for which votes will be calculated.
results	Array where the result of the calculation will be written.
flags	Flags for defining the type of RTrees.

◆ load() [1/2]

static new RTrees OpenCVForUnity.MlModule.RTrees.load	(	string	filepath,
		string	nodeName
	)

static

Loads and creates a serialized RTree from a file.

Use RTree::save to serialize and store an RTree to disk. Load the RTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier

Parameters

filepath	path to serialized RTree
nodeName	name of node containing the classifier

◆ load() [2/2]

static new RTrees OpenCVForUnity.MlModule.RTrees.load ( string filepath )

static

Loads and creates a serialized RTree from a file.

Use RTree::save to serialize and store an RTree to disk. Load the RTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier

Parameters

filepath	path to serialized RTree
nodeName	name of node containing the classifier

◆ setActiveVarCount()

void OpenCVForUnity.MlModule.RTrees.setActiveVarCount ( int val )

See also: getActiveVarCount

◆ setCalculateVarImportance()

void OpenCVForUnity.MlModule.RTrees.setCalculateVarImportance ( bool val )

See also: getCalculateVarImportance

◆ setTermCriteria()

void OpenCVForUnity.MlModule.RTrees.setTermCriteria ( TermCriteria val )

See also: getTermCriteria

The documentation for this class was generated from the following file:

OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/RTrees.cs

Public Member Functions

Static Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ __fromPtr__()

◆ create()

◆ Dispose()

◆ getActiveVarCount()

◆ getCalculateVarImportance()

◆ getOOBError()

◆ getTermCriteria()

◆ getVarImportance()

◆ getVotes()

◆ load() [1/2]

◆ load() [2/2]

◆ setActiveVarCount()

◆ setCalculateVarImportance()

◆ setTermCriteria()

◆ fromPtr()