Package elki.clustering.kmeans
Class SortMeans.Par<V extends NumberVector>
- java.lang.Object
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- elki.clustering.kmeans.AbstractKMeans.Par<V>
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- elki.clustering.kmeans.SortMeans.Par<V>
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- All Implemented Interfaces:
Parameterizer
- Enclosing class:
- SortMeans<V extends NumberVector>
public static class SortMeans.Par<V extends NumberVector> extends AbstractKMeans.Par<V>
Parameterization class.- Author:
- Erich Schubert
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Field Summary
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Fields inherited from class elki.clustering.kmeans.AbstractKMeans.Par
distance, initializer, k, maxiter, varstat
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Constructor Summary
Constructors Constructor Description Par()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description SortMeans<V>
make()
Make an instance after successful configuration.protected boolean
needsMetric()
Users could use other non-metric distances at their own risk; but some k-means variants make explicit use of the triangle inequality, we emit extra warnings then.-
Methods inherited from class elki.clustering.kmeans.AbstractKMeans.Par
configure, getParameterDistance, getParameterInitialization, getParameterK, getParameterMaxIter, getParameterVarstat
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Method Detail
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needsMetric
protected boolean needsMetric()
Description copied from class:AbstractKMeans.Par
Users could use other non-metric distances at their own risk; but some k-means variants make explicit use of the triangle inequality, we emit extra warnings then.- Overrides:
needsMetric
in classAbstractKMeans.Par<V extends NumberVector>
- Returns:
true
if the algorithm uses triangle inequality
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make
public SortMeans<V> make()
Description copied from interface:Parameterizer
Make an instance after successful configuration.Note: your class should return the exact type, only this very broad interface should use
Object
as return type.- Specified by:
make
in interfaceParameterizer
- Specified by:
make
in classAbstractKMeans.Par<V extends NumberVector>
- Returns:
- a new instance
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