org.bytedeco.javacpp

Class opencv_ml.LogisticRegression

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.opencv_core.Algorithm

org.bytedeco.javacpp.helper.opencv_ml.AbstractStatModel

org.bytedeco.javacpp.opencv_ml.StatModel

org.bytedeco.javacpp.opencv_ml.LogisticRegression

All Implemented Interfaces:

AutoCloseable

Enclosing class:

opencv_ml

@Namespace(value="cv::ml")
public static class opencv_ml.LogisticRegression
extends opencv_ml.StatModel

\brief Implements Logistic Regression classifier.

\sa \ref ml_intro_lr

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields

Modifier and Type	Field and Description
static int	BATCH enum cv::ml::LogisticRegression::Methods
static int	MINI_BATCH enum cv::ml::LogisticRegression::Methods
static int	REG_DISABLE enum cv::ml::LogisticRegression::RegKinds
static int	REG_L1 enum cv::ml::LogisticRegression::RegKinds
static int	REG_L2 enum cv::ml::LogisticRegression::RegKinds

Fields inherited from class org.bytedeco.javacpp.opencv_ml.StatModel

COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
LogisticRegression(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
static opencv_ml.LogisticRegression	create() \brief Creates empty model.
opencv_core.Mat	get_learnt_thetas() \brief This function returns the trained paramters arranged across rows.
int	getIterations()
double	getLearningRate()
int	getMiniBatchSize()
int	getRegularization()
opencv_core.TermCriteria	getTermCriteria()
int	getTrainMethod()
float	predict(opencv_core.Mat samples)
float	predict(opencv_core.Mat samples, opencv_core.Mat results, int flags) \brief Predicts responses for input samples and returns a float type.
float	predict(opencv_core.UMat samples)
float	predict(opencv_core.UMat samples, opencv_core.UMat results, int flags)
void	setIterations(int val) \copybrief getIterations @see getIterations
void	setLearningRate(double val) \copybrief getLearningRate @see getLearningRate
void	setMiniBatchSize(int val) \copybrief getMiniBatchSize @see getMiniBatchSize
void	setRegularization(int val) \copybrief getRegularization @see getRegularization
void	setTermCriteria(opencv_core.TermCriteria val) \copybrief getTermCriteria @see getTermCriteria
void	setTrainMethod(int val) \copybrief getTrainMethod @see getTrainMethod

Methods inherited from class org.bytedeco.javacpp.opencv_ml.StatModel

calcError, calcError, empty, getVarCount, isClassifier, isTrained, train, train, train, train

Methods inherited from class org.bytedeco.javacpp.helper.opencv_ml.AbstractStatModel

loadANN_MLP, loadANN_MLP, loadBoost, loadBoost, loadDTrees, loadDTrees, loadEM, loadEM, loadKNearest, loadKNearest, loadLogisticRegression, loadLogisticRegression, loadNormalBayesClassifier, loadNormalBayesClassifier, loadRTrees, loadRTrees, loadSVM, loadSVM

Methods inherited from class org.bytedeco.javacpp.opencv_core.Algorithm

clear, getDefaultName, position, read, save, save, write

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Field Detail

REG_DISABLE

public static final int REG_DISABLE

enum cv::ml::LogisticRegression::RegKinds

See Also:

Constant Field Values

REG_L1

public static final int REG_L1

enum cv::ml::LogisticRegression::RegKinds

See Also:

Constant Field Values

REG_L2

public static final int REG_L2

enum cv::ml::LogisticRegression::RegKinds

See Also:

Constant Field Values

BATCH

public static final int BATCH

enum cv::ml::LogisticRegression::Methods

See Also:

Constant Field Values

MINI_BATCH

public static final int MINI_BATCH

enum cv::ml::LogisticRegression::Methods

See Also:

Constant Field Values

Constructor Detail

LogisticRegression

public LogisticRegression(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

Method Detail

getLearningRate

public double getLearningRate()

See Also:

setLearningRate

setLearningRate

public void setLearningRate(double val)

\copybrief getLearningRate @see getLearningRate

getIterations

public int getIterations()

See Also:

setIterations

setIterations

public void setIterations(int val)

\copybrief getIterations @see getIterations

getRegularization

public int getRegularization()

See Also:

setRegularization

setRegularization

public void setRegularization(int val)

\copybrief getRegularization @see getRegularization

getTrainMethod

public int getTrainMethod()

See Also:

setTrainMethod

setTrainMethod

public void setTrainMethod(int val)

\copybrief getTrainMethod @see getTrainMethod

getMiniBatchSize

public int getMiniBatchSize()

See Also:

setMiniBatchSize

setMiniBatchSize

public void setMiniBatchSize(int val)

\copybrief getMiniBatchSize @see getMiniBatchSize

getTermCriteria

@ByVal
public opencv_core.TermCriteria getTermCriteria()

See Also:

setTermCriteria

setTermCriteria

public void setTermCriteria(@ByVal
                            opencv_core.TermCriteria val)

\copybrief getTermCriteria @see getTermCriteria

predict

public float predict(@ByVal
                     opencv_core.Mat samples,
                     @ByVal(nullValue="cv::OutputArray(cv::noArray())")
                     opencv_core.Mat results,
                     int flags)

\brief Predicts responses for input samples and returns a float type.

Overrides:

predict in class opencv_ml.StatModel

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.

predict

public float predict(@ByVal
                     opencv_core.Mat samples)

Overrides:

predict in class opencv_ml.StatModel

predict

public float predict(@ByVal
                     opencv_core.UMat samples,
                     @ByVal(nullValue="cv::OutputArray(cv::noArray())")
                     opencv_core.UMat results,
                     int flags)

Overrides:

predict in class opencv_ml.StatModel

predict

public float predict(@ByVal
                     opencv_core.UMat samples)

Overrides:

predict in class opencv_ml.StatModel

get_learnt_thetas

@ByVal
public opencv_core.Mat get_learnt_thetas()

\brief This function returns the trained paramters arranged across rows.

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

create

@opencv_core.Ptr
public static opencv_ml.LogisticRegression create()

\brief Creates empty model.

Creates Logistic Regression model with parameters given.