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Common interface for score-based binary classifiers. A binary classifier can predict whether or not an instance belongs to a class based on a decision score (a real number) that measures the association of the input with the negative and positive class.

Accord (in Accord.dll) Version: 3.8.0

public interface IBinaryScoreClassifier<TInput> : IBinaryClassifier<TInput>, 
	IMulticlassClassifier<TInput>, IMultilabelClassifier<TInput>, IMultilabelClassifier<TInput, int[]>, 
	IClassifier<TInput, int[]>, IClassifier, ITransform<TInput, int[]>, 
	ICovariantTransform<TInput, int[]>, ITransform, IMultilabelClassifier<TInput, bool[]>, 
	IClassifier<TInput, bool[]>, ITransform<TInput, bool[]>, 
	ICovariantTransform<TInput, bool[]>, IMultilabelClassifier<TInput, double[]>, 
	IClassifier<TInput, double[]>, ITransform<TInput, double[]>, 
	ICovariantTransform<TInput, double[]>, IMulticlassClassifier<TInput, int>, 
	IClassifier<TInput, int>, ITransform<TInput, int>, ICovariantTransform<TInput, int>, 
	IMulticlassClassifier<TInput, double>, IClassifier<TInput, double>, 
	ITransform<TInput, double>, ICovariantTransform<TInput, double>, 
	IClassifier<TInput, bool>, ITransform<TInput, bool>, 
	ICovariantTransform<TInput, bool>, IMulticlassOutScoreClassifier<TInput, bool>, 
	IMulticlassScoreClassifierBase<TInput, bool>, IMultilabelOutScoreClassifier<TInput, bool>, 
	IMultilabelScoreClassifierBase<TInput, bool>, IMulticlassScoreClassifier<TInput>, IMulticlassScoreClassifier<TInput, int>, 
	IMulticlassOutScoreClassifier<TInput, int>, IMulticlassScoreClassifierBase<TInput, int>, IMultilabelOutScoreClassifier<TInput, int>, 
	IMultilabelScoreClassifierBase<TInput, int>, IMulticlassRefScoreClassifier<TInput, int[]>, IMultilabelRefScoreClassifier<TInput, int[]>, 
	IMultilabelScoreClassifierBase<TInput, int[]>, IMulticlassScoreClassifier<TInput, double>, 
	IMulticlassOutScoreClassifier<TInput, double>, IMulticlassScoreClassifierBase<TInput, double>, 
	IMultilabelOutScoreClassifier<TInput, double>, IMultilabelScoreClassifierBase<TInput, double>, 
	IMulticlassRefScoreClassifier<TInput, double[]>, IMultilabelRefScoreClassifier<TInput, double[]>, 
	IMultilabelScoreClassifierBase<TInput, double[]>, IMulticlassRefScoreClassifier<TInput, bool[]>, 
	IMultilabelRefScoreClassifier<TInput, bool[]>, IMultilabelScoreClassifierBase<TInput, bool[]>, 
	IMultilabelScoreClassifier<TInput>, IMultilabelScoreClassifier<TInput, int>, IMultilabelScoreClassifier<TInput, double>

Public Interface IBinaryScoreClassifier(Of TInput)
	Inherits IBinaryClassifier(Of TInput), IMulticlassClassifier(Of TInput), 
	IMultilabelClassifier(Of TInput), IMultilabelClassifier(Of TInput, Integer()), 
	IClassifier(Of TInput, Integer()), IClassifier, ITransform(Of TInput, Integer()), 
	ICovariantTransform(Of TInput, Integer()), ITransform, IMultilabelClassifier(Of TInput, Boolean()), 
	IClassifier(Of TInput, Boolean()), ITransform(Of TInput, Boolean()), 
	ICovariantTransform(Of TInput, Boolean()), IMultilabelClassifier(Of TInput, Double()), 
	IClassifier(Of TInput, Double()), ITransform(Of TInput, Double()), 
	ICovariantTransform(Of TInput, Double()), IMulticlassClassifier(Of TInput, Integer), 
	IClassifier(Of TInput, Integer), ITransform(Of TInput, Integer), 
	ICovariantTransform(Of TInput, Integer), IMulticlassClassifier(Of TInput, Double), 
	IClassifier(Of TInput, Double), ITransform(Of TInput, Double), 
	ICovariantTransform(Of TInput, Double), IClassifier(Of TInput, Boolean), 
	ITransform(Of TInput, Boolean), ICovariantTransform(Of TInput, Boolean), 
	IMulticlassOutScoreClassifier(Of TInput, Boolean), IMulticlassScoreClassifierBase(Of TInput, Boolean), 
	IMultilabelOutScoreClassifier(Of TInput, Boolean), IMultilabelScoreClassifierBase(Of TInput, Boolean), 
	IMulticlassScoreClassifier(Of TInput), IMulticlassScoreClassifier(Of TInput, Integer), 
	IMulticlassOutScoreClassifier(Of TInput, Integer), IMulticlassScoreClassifierBase(Of TInput, Integer), 
	IMultilabelOutScoreClassifier(Of TInput, Integer), IMultilabelScoreClassifierBase(Of TInput, Integer), 
	IMulticlassRefScoreClassifier(Of TInput, Integer()), IMultilabelRefScoreClassifier(Of TInput, Integer()), 
	IMultilabelScoreClassifierBase(Of TInput, Integer()), IMulticlassScoreClassifier(Of TInput, Double), 
	IMulticlassOutScoreClassifier(Of TInput, Double), IMulticlassScoreClassifierBase(Of TInput, Double), 
	IMultilabelOutScoreClassifier(Of TInput, Double), IMultilabelScoreClassifierBase(Of TInput, Double), 
	IMulticlassRefScoreClassifier(Of TInput, Double()), IMultilabelRefScoreClassifier(Of TInput, Double()), 
	IMultilabelScoreClassifierBase(Of TInput, Double()), IMulticlassRefScoreClassifier(Of TInput, Boolean()), 
	IMultilabelRefScoreClassifier(Of TInput, Boolean()), IMultilabelScoreClassifierBase(Of TInput, Boolean()), 
	IMultilabelScoreClassifier(Of TInput), IMultilabelScoreClassifier(Of TInput, Integer), 
	IMultilabelScoreClassifier(Of TInput, Double)

TInput

The data type for the input data. Default is double[].

The IBinaryScoreClassifierTInput type exposes the following members.

Computes a class-label decision for a given input.

Computes class-label decisions for each vector in the given input.

Computes class-label decisions for each vector in the given input.

Computes class-label decisions for the given input.

Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier).

Computes a numerical score measuring the association between each of the given input vectors and their respective most strongly associated classes.

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.

Computes a numerical score measuring the association between each of the given input vectors and their respective most strongly associated classes.

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.

Computes a numerical score measuring the association between the given input vector and a given classIndex.

Computes a numerical score measuring the association between each of the given input vectors and the given classIndex.

Computes a numerical score measuring the association between each of the given input vectors and the given classIndex.

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.

Computes a numerical score measuring the association between each of the given input vectors and the given classIndex.

Computes a numerical score measuring the association between each of the given input vectors and the given classIndex.

Computes a numerical score measuring the association between the given input vector and each class.

Computes a numerical score measuring the association between each of the given input vectors and each possible class.

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.

Computes a numerical score measuring the association between the given input vector and each class.

Computes a numerical score measuring the association between each of the given input vectors and each possible class.

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.

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.

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.

Views this instance as a multi-class distance classifier, giving access to more advanced methods, such as the prediction of integer labels.

Views this instance as a multi-class distance classifier, giving access to more advanced methods, such as the prediction of integer labels.

Views this instance as a multi-label classifier, giving access to more advanced methods, such as the prediction of one-hot vectors.

Applies the transformation to an input, producing an associated output.

Applies the transformation to a set of input vectors, producing an associated set of output vectors.

Applies the transformation to a set of input vectors, producing an associated set of output vectors.

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