Class LogisticRegression

Namespace

Emgu.CV.ML

Assembly

Emgu.CV.dll

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

public class LogisticRegression : UnmanagedObject, IDisposable, IStatModel, IAlgorithm

Inheritance

object

DisposableObject

UnmanagedObject

LogisticRegression

Implements

IDisposable

IStatModel

IAlgorithm

Inherited Members

UnmanagedObject._ptr

UnmanagedObject.Ptr

DisposableObject.Dispose()

DisposableObject.ReleaseManagedResources()

object.GetType()

object.MemberwiseClone()

object.ToString()

object.Equals(object)

object.Equals(object, object)

object.ReferenceEquals(object, object)

object.GetHashCode()

Extension Methods

AlgorithmExtensions.Clear(IAlgorithm)

AlgorithmExtensions.GetDefaultName(IAlgorithm)

AlgorithmExtensions.IsEmpty(IAlgorithm)

AlgorithmExtensions.Load(IAlgorithm, string, string, string)

AlgorithmExtensions.LoadFromString(IAlgorithm, string, string, string)

AlgorithmExtensions.Read(IAlgorithm, FileNode)

AlgorithmExtensions.Save(IAlgorithm, string)

AlgorithmExtensions.SaveToString(IAlgorithm, string)

AlgorithmExtensions.Write(IAlgorithm, FileStorage, string)

AlgorithmExtensions.Write(IAlgorithm, FileStorage)

StatModelExtensions.Predict(IStatModel, IInputArray, IOutputArray, int)

StatModelExtensions.Train(IStatModel, IInputArray, DataLayoutType, IInputArray)

StatModelExtensions.Train(IStatModel, TrainData, int)

Constructors

LogisticRegression()

Initializes a new instance of the LogisticRegression class.

public LogisticRegression()

Properties

AlgorithmPtr

Return the pointer to the algorithm object

public nint AlgorithmPtr { get; }

Property Value

nint

Iterations

Number of iterations

public int Iterations { get; set; }

Property Value

int

LearningRate

Learning rate

public double LearningRate { get; set; }

Property Value

double

MiniBatchSize

Specifies the number of training samples taken in each step of Mini-Batch Gradient Descent

public int MiniBatchSize { get; set; }

Property Value

int

Regularization

Kind of regularization to be applied

public LogisticRegression.RegularizationMethod Regularization { get; set; }

Property Value

LogisticRegression.RegularizationMethod

StatModelPtr

Return the pointer to the StatModel object

public nint StatModelPtr { get; }

Property Value

nint

TermCriteria

Termination criteria of the algorithm

public MCvTermCriteria TermCriteria { get; set; }

Property Value

MCvTermCriteria

TrainMethod

Kind of training method to be applied

public LogisticRegression.TrainType TrainMethod { get; set; }

Property Value

LogisticRegression.TrainType

Methods

DisposeObject()

Release the unmanaged resources

protected override void DisposeObject()