BaseKNearestNeighborsTModel, TInput, TDistance Class

Base class for K-Nearest Neighbor (k-NN) algorithms.

Inheritance Hierarchy

SystemObject
  Accord.MachineLearningTransformBaseTInput, Int32
    Accord.MachineLearningClassifierBaseTInput, Int32
      Accord.MachineLearningMulticlassClassifierBaseTInput
        Accord.MachineLearningMulticlassScoreClassifierBaseTInput
          Accord.MachineLearningBaseKNearestNeighborsTModel, TInput, TDistance
            Accord.MachineLearningKNearestNeighbors
            Accord.MachineLearningKNearestNeighborsTInput

Namespace: Accord.MachineLearning
Assembly: Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0

Syntax

Copy

[SerializableAttribute]
public abstract class BaseKNearestNeighbors<TModel, TInput, TDistance> : MulticlassScoreClassifierBase<TInput>, 
	ISupervisedMulticlassLearning<TModel, TInput>, ISupervisedMultilabelLearning<TModel, TInput>, ISupervisedLearning<TModel, TInput, int[]>, 
	ISupervisedLearning<TModel, TInput, bool[]>, ISupervisedLearning<TModel, TInput, int>
where TModel : BaseKNearestNeighbors<TModel, TInput, TDistance>
where TDistance : Object, IDistance<TInput>

<SerializableAttribute>
Public MustInherit Class BaseKNearestNeighbors(Of TModel As BaseKNearestNeighbors(Of TModel, TInput, TDistance), TInput, TDistance As {Object, IDistance(Of TInput)})
	Inherits MulticlassScoreClassifierBase(Of TInput)
	Implements ISupervisedMulticlassLearning(Of TModel, TInput), ISupervisedMultilabelLearning(Of TModel, TInput), 
	ISupervisedLearning(Of TModel, TInput, Integer()), ISupervisedLearning(Of TModel, TInput, Boolean()), 
	ISupervisedLearning(Of TModel, TInput, Integer)

Request Example View Source

Type Parameters

TModel: The type of the model being learned.
TInput: The type of the input data.
TDistance: The type for distance functions that can be used with this algorithm.

The BaseKNearestNeighborsTModel, TInput, TDistance type exposes the following members.

Constructors

	Name	Description
	BaseKNearestNeighborsTModel, TInput, TDistance	Initializes a new instance of the BaseKNearestNeighborsTModel, TInput, TDistance class.

Top

Properties

	Name	Description
	Distance	Gets or sets the distance function used as a distance metric between data points.
	Inputs	Gets the set of points given as input of the algorithm.
	K	Gets or sets the number of nearest neighbors to be used in the decision. Default is 5.
	NumberOfClasses	Gets the number of classes expected and recognized by the classifier. (Inherited from ClassifierBaseTInput, TClasses.)
	NumberOfInputs	Gets the number of inputs accepted by the model. (Inherited from TransformBaseTInput, TOutput.)
	NumberOfOutputs	Gets the number of outputs generated by the model. (Inherited from TransformBaseTInput, TOutput.)
	Outputs	Gets the set of labels associated with each Inputs point.
	Token	Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.

Top

Methods

	Name	Description
	Decide(TInput)	Computes class-label decisions for a given set of input vectors. (Inherited from ClassifierBaseTInput, TClasses.)
	Decide(TInput)	Computes a class-label decision for a given input. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Decide(TInput, TClasses)	Computes a class-label decision for a given input. (Inherited from ClassifierBaseTInput, TClasses.)
	Decide(TInput, Boolean)	Computes class-label decisions for the given input. (Inherited from MulticlassClassifierBaseTInput.)
	Decide(TInput, Double)	Computes class-label decisions for the given input. (Inherited from MulticlassClassifierBaseTInput.)
	Decide(TInput, Int32)	Computes class-label decisions for the given input. (Inherited from MulticlassClassifierBaseTInput.)
	Decide(TInput, Double)	Computes a class-label decision for a given input. (Inherited from MulticlassClassifierBaseTInput.)
	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.)
	GetNearestNeighbors	Gets the top K points that are the closest to a given input.
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Learn(TInput, Boolean, Double)	Learns a model that can map the given inputs to the given outputs.
	Learn(TInput, Int32, Double)	Learns a model that can map the given inputs to the given outputs.
	Learn(TInput, Int32, Double)	Learns a model that can map the given inputs to the given outputs.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	Score(TInput)	Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier). (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput)	Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier). (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Overrides MulticlassScoreClassifierBaseTInputScore(TInput, Int32).)
	Score(TInput, Int32)	Predicts a class label for the input vector, returning a numerical score measuring the strength of association of the input vector to its most strongly related class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Double)	Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier). (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32)	Predicts a class label for each input vector, returning a numerical score measuring the strength of association of the input vector to the most strongly related class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32, Double)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32, Double)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Score(TInput, Int32, Double)	Predicts a class label for each input vector, returning a numerical score measuring the strength of association of the input vector to the most strongly related class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput, Int32)	Predicts a class label vector for the given input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput, Int32)	Predicts a class label vector for each input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput, Int32, Double)	Predicts a class label vector for the given input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Scores(TInput, Int32, Double)	Predicts a class label vector for each input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MulticlassScoreClassifierBaseTInput.)
	ToMulticlass	Views this instance as a multi-class generative classifier. (Inherited from MulticlassScoreClassifierBaseTInput.)
	ToMultilabel	Views this instance as a multi-label distance classifier, giving access to more advanced methods, such as the prediction of one-hot vectors. (Inherited from MulticlassScoreClassifierBaseTInput.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	Transform(TInput)	Applies the transformation to an input, producing an associated output. (Inherited from ClassifierBaseTInput, TClasses.)
	Transform(TInput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Inherited from TransformBaseTInput, TOutput.)
	Transform(TInput, TClasses)	Applies the transformation to an input, producing an associated output. (Inherited from ClassifierBaseTInput, TClasses.)
	Transform(TInput, Boolean)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassClassifierBaseTInput.)
	Transform(TInput, Boolean)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassClassifierBaseTInput.)
	Transform(TInput, Double)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassClassifierBaseTInput.)
	Transform(TInput, Double)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassScoreClassifierBaseTInput.)
	Transform(TInput, Double)	Applies the transformation to an input, producing an associated output. (Inherited from MulticlassScoreClassifierBaseTInput.)

Top

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.)

Top

Reference

Accord.MachineLearning Namespace

Accord.MachineLearningKNearestNeighbors

Accord.MachineLearningKNearestNeighborsTInput

BaseKNearestNeighborsAddLanguageSpecificTextSet("LST92D286CD_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TModel, TInput, TDistanceAddLanguageSpecificTextSet("LST92D286CD_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

BaseKNearestNeighborsTModel, TInput, TDistance Class