Package | Description |
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de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain |
Clustering algorithms for uncertain data.
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de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods
Methods that detect outliers in subspaces (projections) of the data set.
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de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms.
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de.lmu.ifi.dbs.elki.algorithm.timeseries |
Algorithms for change point detection in time series.
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de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types
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de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms
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de.lmu.ifi.dbs.elki.evaluation.clustering |
Evaluation of clustering results
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de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
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de.lmu.ifi.dbs.elki.result.textwriter.writers |
Serialization handlers for individual data types.
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Modifier and Type | Class and Description |
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static class |
RepresentativeUncertainClustering.RepresentativenessEvaluation
Representativeness evaluation result.
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Modifier and Type | Class and Description |
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static class |
SOD.SODModel
SOD Model class
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Modifier and Type | Class and Description |
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static class |
EvaluateRetrievalPerformance.RetrievalPerformanceResult
Result object for MAP scores.
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Modifier and Type | Class and Description |
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class |
ChangePoints
Change point detection result Used by change or trend detection algorithms
TODO: we need access to the data labels / timestamp information!
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Modifier and Type | Class and Description |
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class |
Cluster<M extends Model>
Generic cluster class, that may or not have hierarchical information.
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Modifier and Type | Class and Description |
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class |
CoreObjectsModel
Cluster model using "core" objects.
|
class |
CorrelationAnalysisSolution<V extends NumberVector>
A solution of correlation analysis is a matrix of equations describing the
dependencies.
|
class |
CorrelationModel
Cluster model using a filtered PCA result and an centroid.
|
class |
DimensionModel
Cluster model additionally providing a cluster dimensionality.
|
class |
EMModel
Cluster model of an EM cluster, providing a mean and a full covariance
Matrix.
|
class |
GeneratorModel
Cluster model for synthetically generated data.
|
class |
KMeansModel
Trivial subclass of the
MeanModel that indicates the clustering to be
produced by k-means (so the Voronoi cell visualization is sensible). |
class |
LinearEquationModel
Cluster model containing a linear equation system for the cluster.
|
class |
MeanModel
Cluster model that stores a mean for the cluster.
|
class |
MedoidModel
Cluster model that stores a mean for the cluster.
|
class |
SimplePrototypeModel<V>
Cluster model that stores a prototype for each cluster.
|
class |
SubspaceModel
Model for Subspace Clusters.
|
Modifier and Type | Class and Description |
---|---|
static class |
EvaluateClustering.ScoreResult
Result object for outlier score judgements.
|
Modifier and Type | Class and Description |
---|---|
class |
AssociationRuleResult
Result class for association rule mining
|
class |
EvaluationResult
Abstract evaluation result.
|
class |
FrequentItemsetsResult
Result class for frequent itemset mining algorithms.
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Modifier and Type | Method and Description |
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void |
TextWriterTextWriteable.write(TextWriterStream out,
java.lang.String label,
TextWriteable obj)
Use the objects own text serialization.
|
Copyright © 2019 ELKI Development Team. License information.