HammingLoss Class

Mean Accuracy loss, also known as zero-one-loss per class. Equivalent to ZeroOneLoss but for multi-label classifiers.

Inheritance Hierarchy

SystemObject
  Accord.Math.Optimization.LossesLossBaseInt32, Int32, Double
    Accord.Math.Optimization.LossesLossBaseInt32
      Accord.Math.Optimization.LossesHammingLoss

Namespace: Accord.Math.Optimization.Losses
Assembly: Accord.Math (in Accord.Math.dll) Version: 3.8.0

Syntax

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[SerializableAttribute]
public class HammingLoss : LossBase<int[][]>, 
	ILoss<bool[][]>, ILoss<bool[][], double>, 
	ILoss<double[][]>, ILoss<double[][], double>, 
	ILoss<int[]>, ILoss<int[], double>

<SerializableAttribute>
Public Class HammingLoss
	Inherits LossBase(Of Integer()())
	Implements ILoss(Of Boolean()()), ILoss(Of Boolean()(), Double), 
	ILoss(Of Double()()), ILoss(Of Double()(), Double), 
	ILoss(Of Integer()), ILoss(Of Integer(), Double)

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The HammingLoss type exposes the following members.

Constructors

	Name	Description
	HammingLoss(Boolean)	Initializes a new instance of the HammingLoss class.
	HammingLoss(Double)	Initializes a new instance of the HammingLoss class.
	HammingLoss(Int32)	Initializes a new instance of the HammingLoss class.
	HammingLoss(Int32)	Initializes a new instance of the HammingLoss class.

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Properties

	Name	Description
	Expected	Gets the expected outputs (the ground truth). (Inherited from LossBaseTInput, TScore, TLoss.)
	Mean	Gets or sets a value indicating whether the mean accuracy loss should be computed. Default is true.

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Methods

	Name	Description
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Loss(Boolean)	Computes the loss between the expected values (ground truth) and the given actual values that have been predicted.
	Loss(Double)	Computes the loss between the expected values (ground truth) and the given actual values that have been predicted.
	Loss(Int32)	Computes the loss between the expected values (ground truth) and the given actual values that have been predicted.
	Loss(Int32)	Computes the loss between the expected values (ground truth) and the given actual values that have been predicted. (Overrides LossBaseTInput, TScore, TLossLoss(TScore).)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Extension Methods

	Name	Description
	HasMethod	Checks whether an object implements a method with the given name. (Defined by ExtensionMethods.)
	IsEqual	Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices. (Defined by Matrix.)
	To(Type)	Overloaded. Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime. (Defined by ExtensionMethods.)
	ToT	Overloaded. Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime. (Defined by ExtensionMethods.)

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Reference

Accord.Math.Optimization.Losses Namespace