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DaviesBouldinIndexTInstance Class

Implements the internal evaluation method in [1] that measures the "ratio of the within cluster scatter to the between cluster separation" [2].
Inheritance Hierarchy
SystemObject
  Aglomera.Evaluation.InternalDaviesBouldinIndexTInstance

Namespace:  Aglomera.Evaluation.Internal
Assembly:  Aglomera (in Aglomera.dll) Version: 1.1.0
Syntax
C#
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public class DaviesBouldinIndex<TInstance> : IInternalEvaluationCriterion<TInstance>
where TInstance : Object, IComparable<TInstance>
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Type Parameters

TInstance
The type of instance considered.

The DaviesBouldinIndexTInstance type exposes the following members.

Constructors
  NameDescription
Public methodDaviesBouldinIndexTInstance
Creates a new DaviesBouldinIndexTInstance with given dissimilarity metric.
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Properties
  NameDescription
Public propertyDissimilarityMetric
Gets the metric used by this criterion to measure the dissimilarity / distance between cluster elements.
Public propertyDistanceExponent
Gets or sets the distance exponent.
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Methods
  NameDescription
Public methodEquals (Inherited from Object.)
Public methodEvaluate
Evaluates the given ClusterSetTInstance partition according to this evaluation criterion.
Protected methodFinalize (Inherited from Object.)
Public methodGetHashCode (Inherited from Object.)
Public methodGetType (Inherited from Object.)
Protected methodMemberwiseClone (Inherited from Object.)
Public methodToString (Inherited from Object.)
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Remarks
"It happens to be the average similarity between each cluster and its most similar one, averaged over all the clusters[...]. This affirms the idea that no cluster has to be similar to another, and hence the best clustering scheme essentially minimizes the Davies–Bouldin (BD) index" [2]. Notes: - This implementation corresponds to - BD so that a higher index provides a better partitioning. - This implementation returns double.Nan if the partition contains singleton clusters (undefined dispersion). References: [1] - Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE transactions on pattern analysis and machine intelligence, (2), 224-227. [2] - https://en.wikipedia.org/wiki/Davies%E2%80%93Bouldin_index
See Also