OpenCVForUnity.MlModule.KNearest Class Reference

The class implements K-Nearest Neighbors model. More...

Public Member Functions
float	findNearest (Mat samples, int k, Mat results)
	Finds the neighbors and predicts responses for input vectors.
float	findNearest (Mat samples, int k, Mat results, Mat neighborResponses)
	Finds the neighbors and predicts responses for input vectors.
float	findNearest (Mat samples, int k, Mat results, Mat neighborResponses, Mat dist)
	Finds the neighbors and predicts responses for input vectors.
int	getAlgorithmType ()
int	getDefaultK ()
int	getEmax ()
bool	getIsClassifier ()
void	setAlgorithmType (int val)
void	setDefaultK (int val)
void	setEmax (int val)
void	setIsClassifier (bool 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.
virtual float	predict (Mat samples)
	Predicts response(s) for the provided sample(s)
virtual float	predict (Mat samples, Mat results)
	Predicts response(s) for the provided sample(s)
virtual float	predict (Mat samples, Mat results, int flags)
	Predicts response(s) for the provided sample(s)
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 KNearest	__fromPtr__ (IntPtr addr)
static KNearest	create ()
	Creates the empty model.
static KNearest	load (string filepath)
	Loads and creates a serialized knearest 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)

Static Public Attributes
const int	BRUTE_FORCE = 1
const int	KDTREE = 2
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

The class implements K-Nearest Neighbors model.

See also

ml_intro_knn

Member Function Documentation

__fromPtr__()

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

static

create()

static KNearest OpenCVForUnity.MlModule.KNearest.create ( )

static

Creates the empty model.

The static method creates empty KNearest classifier. It should be then trained using StatModel.train method.

Dispose()

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

protectedvirtual

Reimplemented from OpenCVForUnity.CoreModule.Algorithm.

findNearest() [1/3]

float OpenCVForUnity.MlModule.KNearest.findNearest	(	Mat	samples,
		int	k,
		Mat	results )

Finds the neighbors and predicts responses for input vectors.

Parameters

samples	Input samples stored by rows. It is a single-precision floating-point matrix of <number_of_samples> * k size.
k	Number of used nearest neighbors. Should be greater than 1.
results	Vector with results of prediction (regression or classification) for each input sample. It is a single-precision floating-point vector with <number_of_samples> elements.
neighborResponses	Optional output values for corresponding neighbors. It is a single- precision floating-point matrix of <number_of_samples> * k size.
dist	Optional output distances from the input vectors to the corresponding neighbors. It is a single-precision floating-point matrix of <number_of_samples> * k size.

For each input vector (a row of the matrix samples), the method finds the k nearest neighbors. In case of regression, the predicted result is a mean value of the particular vector's neighbor responses. In case of classification, the class is determined by voting.

For each input vector, the neighbors are sorted by their distances to the vector.

In case of C++ interface you can use output pointers to empty matrices and the function will allocate memory itself.

If only a single input vector is passed, all output matrices are optional and the predicted value is returned by the method.

The function is parallelized with the TBB library.

findNearest() [2/3]

float OpenCVForUnity.MlModule.KNearest.findNearest	(	Mat	samples,
		int	k,
		Mat	results,
		Mat	neighborResponses )

Finds the neighbors and predicts responses for input vectors.

Parameters

samples	Input samples stored by rows. It is a single-precision floating-point matrix of <number_of_samples> * k size.
k	Number of used nearest neighbors. Should be greater than 1.
results	Vector with results of prediction (regression or classification) for each input sample. It is a single-precision floating-point vector with <number_of_samples> elements.
neighborResponses	Optional output values for corresponding neighbors. It is a single- precision floating-point matrix of <number_of_samples> * k size.
dist	Optional output distances from the input vectors to the corresponding neighbors. It is a single-precision floating-point matrix of <number_of_samples> * k size.

For each input vector (a row of the matrix samples), the method finds the k nearest neighbors. In case of regression, the predicted result is a mean value of the particular vector's neighbor responses. In case of classification, the class is determined by voting.

For each input vector, the neighbors are sorted by their distances to the vector.

In case of C++ interface you can use output pointers to empty matrices and the function will allocate memory itself.

If only a single input vector is passed, all output matrices are optional and the predicted value is returned by the method.

The function is parallelized with the TBB library.

findNearest() [3/3]

float OpenCVForUnity.MlModule.KNearest.findNearest	(	Mat	samples,
		int	k,
		Mat	results,
		Mat	neighborResponses,
		Mat	dist )

Finds the neighbors and predicts responses for input vectors.

Parameters

samples	Input samples stored by rows. It is a single-precision floating-point matrix of <number_of_samples> * k size.
k	Number of used nearest neighbors. Should be greater than 1.
results	Vector with results of prediction (regression or classification) for each input sample. It is a single-precision floating-point vector with <number_of_samples> elements.
neighborResponses	Optional output values for corresponding neighbors. It is a single- precision floating-point matrix of <number_of_samples> * k size.
dist	Optional output distances from the input vectors to the corresponding neighbors. It is a single-precision floating-point matrix of <number_of_samples> * k size.

For each input vector (a row of the matrix samples), the method finds the k nearest neighbors. In case of regression, the predicted result is a mean value of the particular vector's neighbor responses. In case of classification, the class is determined by voting.

For each input vector, the neighbors are sorted by their distances to the vector.

In case of C++ interface you can use output pointers to empty matrices and the function will allocate memory itself.

If only a single input vector is passed, all output matrices are optional and the predicted value is returned by the method.

The function is parallelized with the TBB library.

getAlgorithmType()

int OpenCVForUnity.MlModule.KNearest.getAlgorithmType

(

)

See also

setAlgorithmType

getDefaultK()

int OpenCVForUnity.MlModule.KNearest.getDefaultK

(

)

See also

setDefaultK

getEmax()

int OpenCVForUnity.MlModule.KNearest.getEmax

(

)

See also

setEmax

getIsClassifier()

bool OpenCVForUnity.MlModule.KNearest.getIsClassifier

(

)

See also

setIsClassifier

load()

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

static

Loads and creates a serialized knearest from a file.

Use KNearest.save to serialize and store an KNearest to disk. Load the KNearest from this file again, by calling this function with the path to the file.

Parameters

filepath

path to serialized KNearest

setAlgorithmType()

void OpenCVForUnity.MlModule.KNearest.setAlgorithmType

(

int

val

)

See also

getAlgorithmType

setDefaultK()

void OpenCVForUnity.MlModule.KNearest.setDefaultK

(

int

val

)

See also

getDefaultK

setEmax()

void OpenCVForUnity.MlModule.KNearest.setEmax

(

int

val

)

See also

getEmax

setIsClassifier()

void OpenCVForUnity.MlModule.KNearest.setIsClassifier

(

bool

val

)

See also

getIsClassifier

Member Data Documentation

BRUTE_FORCE

const int OpenCVForUnity.MlModule.KNearest.BRUTE_FORCE = 1

static

KDTREE

const int OpenCVForUnity.MlModule.KNearest.KDTREE = 2

static

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

• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/KNearest.cs