Package elki.clustering.uncertain
Class FDBSCANNeighborPredicate
- java.lang.Object
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- elki.clustering.uncertain.FDBSCANNeighborPredicate
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- All Implemented Interfaces:
NeighborPredicate<DBIDs>
@Reference(authors="Hans-Peter Kriegel, Martin Pfeifle", title="Density-based clustering of uncertain data", booktitle="Proc. 11th ACM Int. Conf. on Knowledge Discovery and Data Mining (SIGKDD)", url="https://doi.org/10.1145/1081870.1081955", bibkey="DBLP:conf/kdd/KriegelP05") public class FDBSCANNeighborPredicate extends java.lang.Object implements NeighborPredicate<DBIDs>
Density-based Clustering of Applications with Noise and Fuzzy objects (FDBSCAN) is an Algorithm to find sets in a fuzzy database that are density-connected with minimum probability.Reference:
Hans-Peter Kriegel, Martin Pfeifle
Density-based clustering of uncertain data
Proc. 11th ACM Int. Conf. on Knowledge Discovery and Data Mining (SIGKDD)This class is a NeighborPredicate presenting this Algorithm in use with
.GeneralizedDBSCAN
Only Euclidean distance is supported, because of the pruning strategy described in the original article which needs minimum and maximum distances of bounding rectangles. Index support is not yet available.
- Since:
- 0.7.0
- Author:
- Alexander Koos, Erich Schubert
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
FDBSCANNeighborPredicate.Instance
Instance of the neighbor predicate.static class
FDBSCANNeighborPredicate.Par
Parameterizer class.
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Field Summary
Fields Modifier and Type Field Description protected double
epsilon
Epsilon radiusprotected RandomFactory
rand
The random generator to draw the samples with.protected int
sampleSize
The size of samplesets that should be drawn for neighborcheck.protected double
threshold
The relative amount of epsilon-close pairings determined by the neighborcheck.
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Constructor Summary
Constructors Constructor Description FDBSCANNeighborPredicate(double epsilon, int sampleSize, double threshold, RandomFactory seed)
Constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description TypeInformation
getInputTypeRestriction()
Input data type restriction.SimpleTypeInformation<DBIDs>
getOutputType()
Output data type information.FDBSCANNeighborPredicate.Instance
instantiate(Database database)
Instantiate for a database.
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Field Detail
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epsilon
protected double epsilon
Epsilon radius
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sampleSize
protected int sampleSize
The size of samplesets that should be drawn for neighborcheck.
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threshold
protected double threshold
The relative amount of epsilon-close pairings determined by the neighborcheck.
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rand
protected RandomFactory rand
The random generator to draw the samples with.
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Constructor Detail
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FDBSCANNeighborPredicate
public FDBSCANNeighborPredicate(double epsilon, int sampleSize, double threshold, RandomFactory seed)
Constructor.- Parameters:
epsilon
- Maximum distancesampleSize
- Sampling sizethreshold
- Threshold on how many samples are within the radiusseed
- Random generator for sampling
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Method Detail
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instantiate
public FDBSCANNeighborPredicate.Instance instantiate(Database database)
Description copied from interface:NeighborPredicate
Instantiate for a database.- Specified by:
instantiate
in interfaceNeighborPredicate<DBIDs>
- Parameters:
database
- Database to instantiate for- Returns:
- Instance
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getInputTypeRestriction
public TypeInformation getInputTypeRestriction()
Description copied from interface:NeighborPredicate
Input data type restriction.- Specified by:
getInputTypeRestriction
in interfaceNeighborPredicate<DBIDs>
- Returns:
- Type restriction
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getOutputType
public SimpleTypeInformation<DBIDs> getOutputType()
Description copied from interface:NeighborPredicate
Output data type information.- Specified by:
getOutputType
in interfaceNeighborPredicate<DBIDs>
- Returns:
- Type information
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