Class DiameterCriterion
- java.lang.Object
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- elki.clustering.hierarchical.birch.DiameterCriterion
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- All Implemented Interfaces:
BIRCHAbsorptionCriterion
@Alias("D") @Reference(authors="T. Zhang, R. Ramakrishnan, M. Livny", title="BIRCH: An Efficient Data Clustering Method for Very Large Databases", booktitle="Proc. 1996 ACM SIGMOD International Conference on Management of Data", url="https://doi.org/10.1145/233269.233324", bibkey="DBLP:conf/sigmod/ZhangRL96") public class DiameterCriterion extends java.lang.Object implements BIRCHAbsorptionCriterion
Average Radius (R) criterion.References:
T. Zhang, R. Ramakrishnan, M. Livny
BIRCH: An Efficient Data Clustering Method for Very Large Databases
Proc. 1996 ACM SIGMOD International Conference on Management of Data- Since:
- 0.7.5
- Author:
- Erich Schubert
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
DiameterCriterion.Par
Parameterization class
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Field Summary
Fields Modifier and Type Field Description static DiameterCriterion
STATIC
Static instance.
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Constructor Summary
Constructors Constructor Description DiameterCriterion()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
squaredCriterion(ClusteringFeature f1, ClusteringFeature f2)
Quality when merging two CFs.double
squaredCriterion(ClusteringFeature f1, NumberVector n)
Quality of a CF when adding a data point
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Field Detail
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STATIC
public static final DiameterCriterion STATIC
Static instance.
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Method Detail
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squaredCriterion
public double squaredCriterion(ClusteringFeature f1, NumberVector n)
Description copied from interface:BIRCHAbsorptionCriterion
Quality of a CF when adding a data point- Specified by:
squaredCriterion
in interfaceBIRCHAbsorptionCriterion
- Parameters:
f1
- Clustering featuren
- Data point- Returns:
- Quality
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squaredCriterion
public double squaredCriterion(ClusteringFeature f1, ClusteringFeature f2)
Description copied from interface:BIRCHAbsorptionCriterion
Quality when merging two CFs.- Specified by:
squaredCriterion
in interfaceBIRCHAbsorptionCriterion
- Parameters:
f1
- First clustering featuref2
- Second clustering feature- Returns:
- Quality
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