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WeightedConfusionMatrix Class

Weighted confusion matrix for multi-class decision problems.
Inheritance Hierarchy
SystemObject
  Accord.Statistics.AnalysisGeneralConfusionMatrix
    Accord.Statistics.AnalysisWeightedConfusionMatrix

Namespace:  Accord.Statistics.Analysis
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.5.0
Syntax
[SerializableAttribute]
public class WeightedConfusionMatrix : GeneralConfusionMatrix
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The WeightedConfusionMatrix type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyChanceAgreement
Chance agreement.
(Inherited from GeneralConfusionMatrix.)
Public propertyChiSquare
Gets the Chi-Square statistic for the contingency table.
(Inherited from GeneralConfusionMatrix.)
Public propertyClasses
Gets the number of classes.
(Inherited from GeneralConfusionMatrix.)
Public propertyColumnProportions
Gets the column marginals (proportions).
(Inherited from GeneralConfusionMatrix.)
Public propertyColumnTotals
Gets the column totals.
(Inherited from GeneralConfusionMatrix.)
Public propertyCramer
Cramer's V association measure.
(Inherited from GeneralConfusionMatrix.)
Public propertyDiagonal
Gets the diagonal of the confusion matrix.
(Inherited from GeneralConfusionMatrix.)
Public propertyExpectedValues
Expected values, or values that could have been generated just by chance.
(Inherited from GeneralConfusionMatrix.)
Public propertyGeometricAgreement
Geometric agreement.
(Inherited from GeneralConfusionMatrix.)
Public propertyKappa
Gets the Kappa coefficient of performance.
(Inherited from GeneralConfusionMatrix.)
Public propertyMatrix
Gets the confusion matrix, in which each element e_ij represents the number of elements from class i classified as belonging to class j.
(Inherited from GeneralConfusionMatrix.)
Public propertyMax
Gets the maximum number of correct matches (the maximum over the diagonal)
(Inherited from GeneralConfusionMatrix.)
Public propertyMin
Gets the minimum number of correct matches (the minimum over the diagonal)
(Inherited from GeneralConfusionMatrix.)
Public propertyOverallAgreement
Overall agreement.
(Inherited from GeneralConfusionMatrix.)
Public propertyPearson
Pearson's contingency coefficient C.
(Inherited from GeneralConfusionMatrix.)
Public propertyPhi
Phi coefficient.
(Inherited from GeneralConfusionMatrix.)
Public propertyProportionMatrix
Gets the confusion matrix in terms of cell percentages.
(Inherited from GeneralConfusionMatrix.)
Public propertyRowProportions
Gets the row marginals (proportions).
(Inherited from GeneralConfusionMatrix.)
Public propertyRowTotals
Gets the row totals.
(Inherited from GeneralConfusionMatrix.)
Public propertySakoda
Sakoda's contingency coefficient V.
(Inherited from GeneralConfusionMatrix.)
Public propertySamples
Gets the number of samples.
(Inherited from GeneralConfusionMatrix.)
Public propertyStandardError
Gets the standard error of the Kappa coefficient of performance.
(Inherited from GeneralConfusionMatrix.)
Public propertyStandardErrorUnderNull
Gets the standard error of the Kappa under the null hypothesis that the underlying Kappa value is 0.
(Inherited from GeneralConfusionMatrix.)
Public propertyTau
Gets the Tau coefficient of performance.
(Inherited from GeneralConfusionMatrix.)
Public propertyTschuprow
Tschuprow's T association measure.
(Inherited from GeneralConfusionMatrix.)
Public propertyVariance
Gets the variance of the Kappa coefficient of performance.
(Inherited from GeneralConfusionMatrix.)
Public propertyVarianceUnderNull
Gets the variance of the Kappa under the null hypothesis that the underlying Kappa value is 0.
(Inherited from GeneralConfusionMatrix.)
Public propertyWeightedChanceAgreement
Chance agreement.
Public propertyWeightedColumnProportions
Gets the column marginals (proportions).
Public propertyWeightedKappa
Gets the Kappa coefficient of performance.
Public propertyWeightedOverallAgreement
Overall agreement.
Public propertyWeightedRowProportions
Gets the row marginals (proportions).
Public propertyWeightedStandardError
Gets the standard error of the WeightedKappa coefficient of performance.
Public propertyWeightedStandardErrorUnderNull
Gets the standard error of the WeightedKappa under the null hypothesis that the underlying Kappa value is 0.
Public propertyWeightedVariance
Gets the variance of the WeightedKappa coefficient of performance.
Public propertyWeightedVarianceUnderNull
Gets the variance of the WeightedKappa under the null hypothesis that the underlying Kappa value is 0.
Public propertyWeights
Gets the Weights matrix.
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Methods
  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodStatic memberLinearWeighting
Creates a new Weighted Confusion Matrix with linear weighting.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodStatic memberQuadraticWeighting
Creates a new Weighted Confusion Matrix with linear weighting.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodToTOverloaded.
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.)
Public Extension MethodToTOverloaded.
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 Matrix.)
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Remarks
See Also