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Jaccard Structure
Jaccard (Index) distance.

Namespace:  Accord.Math.Distances
Assembly:  Accord.Math (in Accord.Math.dll) Version: 3.8.0
Syntax
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[SerializableAttribute]
public struct Jaccard : ISimilarity<double[]>, 
	ISimilarity<double[], double[]>, IDistance<double[]>, 
	IDistance<double[], double[]>
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The Jaccard type exposes the following members.

Methods
  NameDescription
Public methodDistance
Computes the distance d(x,y) between points x and y.
Public methodEquals
Indicates whether this instance and a specified object are equal.
(Inherited from ValueType.)
Public methodGetHashCode
Returns the hash code for this instance.
(Inherited from ValueType.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodSimilarity
Gets a similarity measure between two points.
Public methodToString
Returns the fully qualified type name of this instance.
(Inherited from ValueType.)
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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 MethodTo(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.)
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.)
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Remarks

The Jaccard index, also known as the Jaccard similarity coefficient (originally coined coefficient de communauté by Paul Jaccard), is a statistic used for comparing the similarity and diversity of sample sets. The Jaccard coefficient measures similarity between finite sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets.

References:

See Also