LogisticRegression Class

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ML implements logistic regression, which is a probabilistic classification technique.

Inheritance Hierarchy

Namespace: Emgu.CV.ML
Assembly: Emgu.CV.World (in Emgu.CV.World.dll) Version: 4.0.1.3373 (4.0.1.3373)

Syntax

public class LogisticRegression : UnmanagedObject, 
	IStatModel, IAlgorithm

Public Class LogisticRegression
	Inherits UnmanagedObject
	Implements IStatModel, IAlgorithm

public ref class LogisticRegression : public UnmanagedObject, 
	IStatModel, IAlgorithm

type LogisticRegression =  
    class
        inherit UnmanagedObject
        interface IStatModel
        interface IAlgorithm
    end

The LogisticRegression type exposes the following members.

Constructors

	Name	Description
	LogisticRegression	Initializes a new instance of the LogisticRegression class.

Properties

	Name	Description
	AlgorithmPtr	Return the pointer to the algorithm object
	Iterations	Number of iterations
	LearningRate	Learning rate
	MiniBatchSize	Specifies the number of training samples taken in each step of Mini-Batch Gradient Descent
	Ptr	Pointer to the unmanaged object (Inherited from UnmanagedObject.)
	Regularization	Kind of regularization to be applied
	StatModelPtr	Return the pointer to the StatModel object
	TermCriteria	Termination criteria of the algorithm
	TrainMethod	Kind of training method to be applied

Methods

	Name	Description
	Dispose	The dispose function that implements IDisposable interface (Inherited from DisposableObject.)
	DisposeObject	Release the unmanaged resources (Overrides DisposableObjectDisposeObject.)
	Equals	Determines whether the specified Object is equal to the current Object. (Inherited from Object.)
	Finalize	Destructor (Inherited from DisposableObject.)
	GetHashCode	Serves as a hash function for a particular type. (Inherited from Object.)
	GetType	Gets the type of the current instance. (Inherited from Object.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ReleaseManagedResources	Release the managed resources. This function will be called during the disposal of the current object. override ride this function if you need to call the Dispose() function on any managed IDisposable object created by the current object (Inherited from DisposableObject.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

Fields

	Name	Description
	_ptr	A pointer to the unmanaged object (Inherited from UnmanagedObject.)

Extension Methods

	Name	Description
	Clear	Clear the algorithm (Defined by AlgorithmExtensions.)
	GetDefaultName	Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string. (Defined by AlgorithmExtensions.)
	IsEmpty	Returns true if the Algorithm is empty. e.g. in the very beginning or after unsuccessful read. (Defined by AlgorithmExtensions.)
	Load	Loads algorithm from the file (Defined by AlgorithmExtensions.)
	LoadFromString	Loads algorithm from a String (Defined by AlgorithmExtensions.)
	Predict	Predicts response(s) for the provided sample(s) (Defined by StatModelExtensions.)
	Read	Reads algorithm parameters from a file storage. (Defined by AlgorithmExtensions.)
	Save	Save the algorithm to file (Defined by AlgorithmExtensions.)
	SaveToString	Save the algorithm to a string (Defined by AlgorithmExtensions.)
	Train(TrainData, Int32)	Overloaded. Trains the statistical model. (Defined by StatModelExtensions.)
	Train(IInputArray, DataLayoutType, IInputArray)	Overloaded. Trains the statistical model. (Defined by StatModelExtensions.)
	Write(FileStorage)	Overloaded. Stores algorithm parameters in a file storage (Defined by AlgorithmExtensions.)
	Write(FileStorage, String)	Overloaded. Stores algorithm parameters in a file storage (Defined by AlgorithmExtensions.)