de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Class FDBSCAN

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<Clustering<Model>>

de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN

de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCAN

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<Model>>

@Title(value="FDBSCAN: Density-based Clustering of Applications with Noise on fuzzy objects")
 @Description(value="Algorithm to find density-connected sets in a database consisting of uncertain/fuzzy objects based on the parameters \'minpts\', \'epsilon\', \'samplesize\', and (if used) \'threshold\'")
 @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 FDBSCAN
extends GeneralizedDBSCAN

FDBSCAN is an adaption of DBSCAN for fuzzy (uncertain) objects.

This implementation is based on GeneralizedDBSCAN. All implementation of FDBSCAN functionality is located in the neighbor predicate FDBSCANNeighborPredicate.

Reference:

Hans-Peter Kriegel, Martin Pfeifle
Density-based clustering of uncertain data
Proc. 11th ACM Int. Conf. on Knowledge Discovery and Data Mining (SIGKDD)

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	FDBSCAN.Parameterizer Parameterizer class.

Nested classes/interfaces inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN

GeneralizedDBSCAN.Instance<T>

Field Summary

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN

coremodel, corepred, npred

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Constructor Summary

Constructors

Constructor and Description
FDBSCAN(double epsilon, int sampleSize, double threshold, RandomFactory seed, int minpts) Constructor that initialized GeneralizedDBSCAN.

Method Summary

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN

getInputTypeRestriction, getLogger, run

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

FDBSCAN

public FDBSCAN(double epsilon,
               int sampleSize,
               double threshold,
               RandomFactory seed,
               int minpts)

Constructor that initialized GeneralizedDBSCAN.

Parameters:

epsilon - Epsilon radius

sampleSize - Sample size

threshold - Threshold

seed - Random generator

minpts - MinPts