Package elki
Interface Algorithm
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- All Known Subinterfaces:
Classifier<O>
,ClusteringAlgorithm<C>
,GeneralizedOPTICS
,HierarchicalClusteringAlgorithm
,KMeans<V,M>
,KMedoidsClustering<O>
,OPTICSTypeAlgorithm
,OutlierAlgorithm
,SubspaceClusteringAlgorithm<M>
- All Known Implementing Classes:
ABOD
,AbstractAggarwalYuOutlier
,AbstractBiclustering
,AbstractClassifier
,AbstractCutDendrogram
,AbstractDBOutlier
,AbstractDistanceBasedSpatialOutlier
,AbstractFrequentItemsetAlgorithm
,AbstractHDBSCAN
,AbstractKMeans
,AbstractNeighborhoodOutlier
,AbstractOPTICS
,AbstractProjectedClustering
,AbstractProjectionAlgorithm
,AddSingleScale
,AddUniformScale
,AffinityPropagation
,AggarwalYuEvolutionary
,AggarwalYuNaive
,AGNES
,ALOCI
,AlternatingKMedoids
,Anderberg
,AnnulusKMeans
,APRIORI
,AssociationRuleGeneration
,AveragePrecisionAtK
,BarnesHutTSNE
,BestOfMultipleKMeans
,BetulaGMM
,BetulaGMMWeighted
,BetulaLeafPreClustering
,BetulaLloydKMeans
,BIRCHLeafClustering
,BIRCHLloydKMeans
,BisectingKMeans
,ByLabelClustering
,ByLabelHierarchicalClustering
,ByLabelOrAllInOneClustering
,ByLabelOutlier
,ByModelClustering
,CanopyPreClustering
,CASH
,CBLOF
,CenterOfMassMetaClustering
,CFSFDP
,CFSFDP
,ChengAndChurch
,CKMeans
,CLARA
,CLARANS
,CLINK
,CLIQUE
,ClustersWithNoiseExtraction
,COF
,CompareMeans
,COP
,COPAC
,CTLuGLSBackwardSearchAlgorithm
,CTLuMeanMultipleAttributes
,CTLuMedianAlgorithm
,CTLuMedianMultipleAttributes
,CTLuMoranScatterplotOutlier
,CTLuRandomWalkEC
,CTLuScatterplotOutlier
,CTLuZTestOutlier
,CutDendrogramByHeight
,CutDendrogramByNumberOfClusters
,DBOutlierDetection
,DBOutlierScore
,DBSCAN
,DBSCANOutlierDetection
,DeLiClu
,DependencyDerivator
,DiSH
,DistanceQuantileSampler
,DistanceStatisticsWithClasses
,DistanceStddevOutlier
,DOC
,DWOF
,EagerPAM
,Eclat
,ElkanKMeans
,EM
,EMOutlier
,ERiC
,EuclideanSphericalElkanKMeans
,EuclideanSphericalHamerlyKMeans
,EuclideanSphericalSimplifiedElkanKMeans
,EvaluateRankingQuality
,EvaluateRetrievalPerformance
,ExponionKMeans
,ExternalClustering
,ExternalDoubleOutlierScore
,FastABOD
,FastCLARA
,FastCLARANS
,FastDOC
,FasterCLARA
,FasterMSC
,FasterPAM
,FastMSC
,FastOPTICS
,FastPAM
,FastPAM1
,FDBSCAN
,FeatureBagging
,FlexibleLOF
,FourC
,FPGrowth
,FuzzyCMeans
,GaussianModel
,GaussianUniformMixture
,GeneralizedDBSCAN
,GLOSH
,GMeans
,GreedyKCenter
,GriDBSCAN
,HACAM
,HamerlyKMeans
,HartiganWongKMeans
,HDBSCANHierarchyExtraction
,HDBSCANLinearMemory
,HiCO
,HiCS
,HilOut
,HiSC
,HopkinsStatisticClusteringTendency
,HySortOD
,IDOS
,INFLO
,IsolationForest
,ISOS
,KDEOS
,KDTreeEM
,KDTreeFilteringKMeans
,KDTreePruningKMeans
,KMeansMinusMinus
,KMeansMinusMinusOutlierDetection
,KMeansOutlierDetection
,KMediansLloyd
,KNNClassifier
,KNNDD
,KNNDistancesSampler
,KNNJoin
,KNNKernelDensityMinimaClustering
,KNNOutlier
,KNNSOS
,KNNWeightOutlier
,LBABOD
,LDF
,LDOF
,Leader
,LibSVMOneClassOutlierDetection
,LID
,LinearMemoryNNChain
,LloydKMeans
,LMCLUS
,LocalIsolationCoefficient
,LOCI
,LOF
,LoOP
,LSDBC
,MacQueenKMeans
,MedoidLinkage
,MiniMax
,MiniMaxAnderberg
,MiniMaxNNChain
,NaiveAgglomerativeHierarchicalClustering1
,NaiveAgglomerativeHierarchicalClustering2
,NaiveAgglomerativeHierarchicalClustering3
,NaiveAgglomerativeHierarchicalClustering4
,NaiveMeanShiftClustering
,NNChain
,NoiseAsOutliers
,NullAlgorithm
,OCSVM
,ODIN
,ODIN
,OfflineChangePointDetectionAlgorithm
,OnlineLOF
,OPTICSHeap
,OPTICSList
,OPTICSOF
,OPTICSToHierarchical
,OPTICSXi
,ORCLUS
,OutRankS1
,OUTRES
,P3C
,PAM
,PAMMEDSIL
,PAMSIL
,ParallelGeneralizedDBSCAN
,ParallelKNNOutlier
,ParallelKNNWeightOutlier
,ParallelLloydKMeans
,ParallelLOF
,ParallelSimplifiedLOF
,PreDeCon
,PriorProbabilityClassifier
,PROCLUS
,RankingQualityHistogram
,ReferenceBasedOutlierDetection
,RepresentativeUncertainClustering
,RescaleMetaOutlierAlgorithm
,ReynoldsPAM
,SameSizeKMeans
,ShallotKMeans
,SigniTrendChangeDetection
,SilhouetteOutlierDetection
,SimpleCOP
,SimpleKernelDensityLOF
,SimpleOutlierEnsemble
,SimplifiedElkanKMeans
,SimplifiedHierarchyExtraction
,SimplifiedLOF
,SingleAssignmentKMeans
,SingleAssignmentKMedoids
,SLINK
,SLINKHDBSCANLinearMemory
,SLOM
,SNE
,SNNClustering
,SOD
,SOF
,SortMeans
,SOS
,SphericalElkanKMeans
,SphericalHamerlyKMeans
,SphericalKMeans
,SphericalSimplifiedElkanKMeans
,SphericalSimplifiedHamerlyKMeans
,SphericalSingleAssignmentKMeans
,SUBCLU
,SupportVectorClustering
,SVDD
,TrimmedMeanApproach
,TrivialAllInOne
,TrivialAllNoise
,TrivialAllOutlier
,TrivialAverageCoordinateOutlier
,TrivialGeneratedOutlier
,TrivialNoOutlier
,TSNE
,UKMeans
,VarianceOfVolume
,XMeans
,YinYangKMeans
public interface Algorithm
Specifies the requirements for any algorithm that is to be executable by the main class.Any implementation needs not to take care of input nor output, parsing and so on. Those tasks are performed by the framework. An algorithm simply needs to ask for parameters that are algorithm specific.
- Since:
- 0.1
- Author:
- Arthur Zimek
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Nested Class Summary
Nested Classes Modifier and Type Interface Description static class
Algorithm.Utils
Shared functionality
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Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description default java.lang.Object
autorun(Database database)
Try to auto-run the algorithm on a database by calling a method calledrun
, with an optionalDatabase
first, and with data relations as specified bygetInputTypeRestriction()
.TypeInformation[]
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.
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Method Detail
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autorun
default java.lang.Object autorun(Database database)
Try to auto-run the algorithm on a database by calling a method calledrun
, with an optionalDatabase
first, and with data relations as specified bygetInputTypeRestriction()
.- Parameters:
database
- the database to run the algorithm on- Returns:
- the Result computed by this algorithm
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getInputTypeRestriction
TypeInformation[] getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.- Returns:
- Type restriction
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