ToolsToConfusionMatrixTModel, TInput Method (CrossValidationResultTModel, TInput, Boolean, TInput, Boolean)

Generates a ConfusionMatrix from a set of cross-validation results.

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

Syntax

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public static ConfusionMatrix ToConfusionMatrix<TModel, TInput>(
	this CrossValidationResult<TModel, TInput, bool> cv,
	TInput[] inputs,
	bool[] outputs
)
where TModel : class, Object, ITransform<TInput, bool>

<ExtensionAttribute>
Public Shared Function ToConfusionMatrix(Of TModel As {Class, Object, ITransform(Of TInput, Boolean)}, TInput) ( 
	cv As CrossValidationResult(Of TModel, TInput, Boolean),
	inputs As TInput(),
	outputs As Boolean()
) As ConfusionMatrix

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Parameters

cv: Type: Accord.MachineLearning.PerformanceCrossValidationResultTModel, TInput, Boolean
The cross-validation result.
inputs: Type: TInput
The inputs fed to the cross-validation object.
outputs: Type: SystemBoolean
The outputs fed to the cross-validation object.

Type Parameters

TModel: The type of the model being evaluated.
TInput: The type of the inputs accepted by the model.

Return Value

Type: ConfusionMatrix
A ConfusionMatrix that captures the performance of the model across all validation folds.

Usage Note

In Visual Basic and C#, you can call this method as an instance method on any object of type CrossValidationResultTModel, TInput, Boolean. When you use instance method syntax to call this method, omit the first parameter. For more information, see Extension Methods (Visual Basic) or Extension Methods (C# Programming Guide).

Reference

Tools Class

ToConfusionMatrix Overload

Accord.MachineLearning Namespace