Implements Logistic Regression classifier. More...

Public Member Functions
Mat	get_learnt_thetas ()
	This function returns the trained parameters arranged across rows.

int	getIterations ()

double	getLearningRate ()

int	getMiniBatchSize ()

int	getRegularization ()

TermCriteria	getTermCriteria ()

double double double epsilon	getTermCriteriaAsValueTuple ()

Vec3d	getTermCriteriaAsVec3d ()

int	getTrainMethod ()

override float	predict (Mat samples)
	Predicts responses for input samples and returns a float type.

override float	predict (Mat samples, Mat results)
	Predicts responses for input samples and returns a float type.

override float	predict (Mat samples, Mat results, int flags)
	Predicts responses for input samples and returns a float type.

void	setIterations (int val)

void	setLearningRate (double val)

void	setMiniBatchSize (int val)

void	setRegularization (int val)

void	setTermCriteria (in Vec3d val)

void	setTermCriteria (in(double type, double maxCount, double epsilon) val)

void	setTermCriteria (TermCriteria val)

void	setTrainMethod (int val)

Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel
float	calcError (TrainData data, bool test, Mat resp)
	Computes error on the training or test dataset.

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

int	getVarCount ()
	Returns the number of variables in training samples.

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

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

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

bool	train (TrainData trainData)
	Trains the statistical model.

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

Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
virtual void	clear ()
	Clears the algorithm state.

virtual string	getDefaultName ()

IntPtr	getNativeObjAddr ()

void	save (string filename)

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

void	ThrowIfDisposed ()

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

static LogisticRegression	create ()
	Creates empty model.

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

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

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)

Public Attributes
double double	maxCount

double	type

Static Public Attributes
const int	BATCH = 0

const int	MINI_BATCH = 1

const int	REG_DISABLE = -1

const int	REG_L1 = 0

const int	REG_L2 = 1

Static Public Attributes inherited from OpenCVForUnity.MlModule.StatModel
const int	COMPRESSED_INPUT = 2

const int	PREPROCESSED_INPUT = 4

const int	RAW_OUTPUT = 1

const int	UPDATE_MODEL = 1

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.CoreModule.Algorithm
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 Functions inherited from OpenCVForUnity.MlModule.StatModel
Package Functions inherited from OpenCVForUnity.CoreModule.Algorithm
Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject
Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed `[get, protected set]`

bool	IsEnabledDispose `[get, set]`

Detailed Description

Implements Logistic Regression classifier.

See also: ml_intro_lr

Member Function Documentation

◆ fromPtr()

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

static

◆ create()

static LogisticRegression OpenCVForUnity.MlModule.LogisticRegression.create ( )

static

Creates empty model.

Creates Logistic Regression model with parameters given.

◆ Dispose()

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

protectedvirtual

Reimplemented from OpenCVForUnity.CoreModule.Algorithm.

◆ get_learnt_thetas()

Mat OpenCVForUnity.MlModule.LogisticRegression.get_learnt_thetas ( )

This function returns the trained parameters arranged across rows.

For a two class classification problem, it returns a row matrix. It returns learnt parameters of the Logistic Regression as a matrix of type CV_32F.

◆ getIterations()

int OpenCVForUnity.MlModule.LogisticRegression.getIterations ( )

See also: setIterations

◆ getLearningRate()

double OpenCVForUnity.MlModule.LogisticRegression.getLearningRate ( )

See also: setLearningRate

◆ getMiniBatchSize()

int OpenCVForUnity.MlModule.LogisticRegression.getMiniBatchSize ( )

See also: setMiniBatchSize

◆ getRegularization()

int OpenCVForUnity.MlModule.LogisticRegression.getRegularization ( )

See also: setRegularization

◆ getTermCriteria()

TermCriteria OpenCVForUnity.MlModule.LogisticRegression.getTermCriteria ( )

See also: setTermCriteria

◆ getTermCriteriaAsValueTuple()

double double double epsilon OpenCVForUnity.MlModule.LogisticRegression.getTermCriteriaAsValueTuple ( )

◆ getTermCriteriaAsVec3d()

Vec3d OpenCVForUnity.MlModule.LogisticRegression.getTermCriteriaAsVec3d ( )

See also: setTermCriteria

◆ getTrainMethod()

int OpenCVForUnity.MlModule.LogisticRegression.getTrainMethod ( )

See also: setTrainMethod

◆ load() [1/2]

static LogisticRegression OpenCVForUnity.MlModule.LogisticRegression.load ( string filepath )

static

Loads and creates a serialized LogisticRegression from a file.

Use LogisticRegression.save to serialize and store an LogisticRegression to disk. Load the LogisticRegression 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 LogisticRegression
nodeName	name of node containing the classifier

◆ load() [2/2]

static LogisticRegression OpenCVForUnity.MlModule.LogisticRegression.load	(	string	filepath,
		string	nodeName )

static

Loads and creates a serialized LogisticRegression from a file.

Use LogisticRegression.save to serialize and store an LogisticRegression to disk. Load the LogisticRegression 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 LogisticRegression
nodeName	name of node containing the classifier

◆ predict() [1/3]

override float OpenCVForUnity.MlModule.LogisticRegression.predict ( Mat samples )

virtual

Predicts responses for input samples and returns a float type.

Parameters

samples	The input data for the prediction algorithm. Matrix [m x n], where each row contains variables (features) of one object being classified. Should have data type CV_32F.
results	Predicted labels as a column matrix of type CV_32S.
flags	Not used.

Reimplemented from OpenCVForUnity.MlModule.StatModel.

◆ predict() [2/3]

override float OpenCVForUnity.MlModule.LogisticRegression.predict	(	Mat	samples,
		Mat	results )

virtual

Predicts responses for input samples and returns a float type.

Parameters

samples	The input data for the prediction algorithm. Matrix [m x n], where each row contains variables (features) of one object being classified. Should have data type CV_32F.
results	Predicted labels as a column matrix of type CV_32S.
flags	Not used.

Reimplemented from OpenCVForUnity.MlModule.StatModel.

◆ predict() [3/3]

override float OpenCVForUnity.MlModule.LogisticRegression.predict	(	Mat	samples,
		Mat	results,
		int	flags )

virtual

Predicts responses for input samples and returns a float type.

Parameters

samples	The input data for the prediction algorithm. Matrix [m x n], where each row contains variables (features) of one object being classified. Should have data type CV_32F.
results	Predicted labels as a column matrix of type CV_32S.
flags	Not used.

Reimplemented from OpenCVForUnity.MlModule.StatModel.

◆ setIterations()

void OpenCVForUnity.MlModule.LogisticRegression.setIterations ( int val )

See also: getIterations

◆ setLearningRate()

void OpenCVForUnity.MlModule.LogisticRegression.setLearningRate ( double val )

See also: getLearningRate

◆ setMiniBatchSize()

void OpenCVForUnity.MlModule.LogisticRegression.setMiniBatchSize ( int val )

See also: getMiniBatchSize

◆ setRegularization()

void OpenCVForUnity.MlModule.LogisticRegression.setRegularization ( int val )

See also: getRegularization

◆ setTermCriteria() [1/3]

void OpenCVForUnity.MlModule.LogisticRegression.setTermCriteria ( in Vec3d val )

See also: getTermCriteria

◆ setTermCriteria() [2/3]

void OpenCVForUnity.MlModule.LogisticRegression.setTermCriteria ( in(double type, double maxCount, double epsilon) val )

See also: getTermCriteria

◆ setTermCriteria() [3/3]

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

See also: getTermCriteria

◆ setTrainMethod()

void OpenCVForUnity.MlModule.LogisticRegression.setTrainMethod ( int val )

See also: getTrainMethod

Member Data Documentation

◆ BATCH

const int OpenCVForUnity.MlModule.LogisticRegression.BATCH = 0

static

◆ maxCount

double double OpenCVForUnity.MlModule.LogisticRegression.maxCount

◆ MINI_BATCH

const int OpenCVForUnity.MlModule.LogisticRegression.MINI_BATCH = 1

static

◆ REG_DISABLE

const int OpenCVForUnity.MlModule.LogisticRegression.REG_DISABLE = -1

static

◆ REG_L1

const int OpenCVForUnity.MlModule.LogisticRegression.REG_L1 = 0

static

◆ REG_L2

const int OpenCVForUnity.MlModule.LogisticRegression.REG_L2 = 1

static

◆ type

double OpenCVForUnity.MlModule.LogisticRegression.type

See also: setTermCriteria

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

OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/LogisticRegression.cs
OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/LogisticRegression_Struct.cs
OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/LogisticRegression_ValueTuple.cs

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ __fromPtr__()

◆ create()

◆ Dispose()

◆ get_learnt_thetas()

◆ getIterations()

◆ getLearningRate()

◆ getMiniBatchSize()

◆ getRegularization()

◆ getTermCriteria()

◆ getTermCriteriaAsValueTuple()

◆ getTermCriteriaAsVec3d()

◆ getTrainMethod()

◆ load() [1/2]

◆ load() [2/2]

◆ predict() [1/3]

◆ predict() [2/3]

◆ predict() [3/3]

◆ setIterations()

◆ setLearningRate()

◆ setMiniBatchSize()

◆ setRegularization()

◆ setTermCriteria() [1/3]

◆ setTermCriteria() [2/3]

◆ setTermCriteria() [3/3]

◆ setTrainMethod()

Member Data Documentation

◆ BATCH

◆ maxCount

◆ MINI_BATCH

◆ REG_DISABLE

◆ REG_L1

◆ REG_L2

◆ type

◆ fromPtr()