Class Boost

Namespace

OpenCvSharp.ML

Assembly

OpenCvSharp.dll

Boosted tree classifier derived from DTrees

public class Boost : DTrees, IDisposable, ICvPtrHolder

Inheritance

object

DisposableObject

DisposableCvObject

Algorithm

StatModel

DTrees

Boost

Implements

IDisposable

ICvPtrHolder

Inherited Members

DTrees.MaxCategories

DTrees.MaxDepth

DTrees.MinSampleCount

DTrees.CVFolds

DTrees.UseSurrogates

DTrees.Use1SERule

DTrees.TruncatePrunedTree

DTrees.RegressionAccuracy

DTrees.Priors

DTrees.GetRoots()

DTrees.GetNodes()

DTrees.GetSplits()

DTrees.GetSubsets()

StatModel.GetVarCount()

StatModel.Empty()

StatModel.IsTrained()

StatModel.IsClassifier()

StatModel.Train(TrainData, int)

StatModel.Train(InputArray, SampleTypes, InputArray)

StatModel.CalcError(TrainData, bool, OutputArray)

StatModel.Predict(InputArray, OutputArray, StatModel.Flags)

Algorithm.Write(FileStorage)

Algorithm.Read(FileNode)

Algorithm.Save(string)

Algorithm.GetDefaultName()

DisposableCvObject.ptr

DisposableCvObject.DisposeUnmanaged()

DisposableCvObject.CvPtr

DisposableObject.DataHandle

DisposableObject.IsDisposed

DisposableObject.IsEnabledDispose

DisposableObject.AllocatedMemory

DisposableObject.AllocatedMemorySize

DisposableObject.Dispose()

DisposableObject.Dispose(bool)

DisposableObject.AllocGCHandle(object)

DisposableObject.AllocMemory(int)

DisposableObject.NotifyMemoryPressure(long)

DisposableObject.ThrowIfDisposed()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

Boost(nint)

Creates instance by raw pointer cv::ml::Boost*

protected Boost(nint p)

Parameters

p nint

Properties

BoostType

Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL.

public Boost.Types BoostType { get; set; }

Property Value

Boost.Types

WeakCount

The number of weak classifiers. Default value is 100.

public int WeakCount { get; set; }

Property Value

int

WeightTrimRate

A threshold between 0 and 1 used to save computational time. Samples with summary weight \f$\leq 1 - weight_trim_rate do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.

public double WeightTrimRate { get; set; }

Property Value

double

Methods

Create()

Creates the empty model.

public static Boost Create()

Returns

Boost

DisposeManaged()

Releases managed resources

protected override void DisposeManaged()

Load(string)

Loads and creates a serialized model from a file.

public static Boost Load(string filePath)

Parameters

filePath string

Returns

Boost

LoadFromString(string)

Loads algorithm from a String.

public static Boost LoadFromString(string strModel)

Parameters

strModel string

he string variable containing the model you want to load.

Returns

Boost