Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical | |
de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
de.lmu.ifi.dbs.elki.evaluation.clustering |
Evaluation of clustering results.
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de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments |
Pair-segment analysis of multiple clusterings.
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de.lmu.ifi.dbs.elki.evaluation.index |
Simple index evaluation methods
|
de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
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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.optics |
Result classes for OPTICS.
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de.lmu.ifi.dbs.elki.result.outlier |
Outlier result classes
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de.lmu.ifi.dbs.elki.visualization.projections |
Visualization projections
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de.lmu.ifi.dbs.elki.workflow |
Work flow packages, e.g. following the usual KDD model, closely related to CRISP-DM
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Modifier and Type | Class and Description |
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class |
PointerHierarchyRepresentationResult<D extends Distance<D>>
The pointer representation of a hierarchical clustering.
|
Modifier and Type | Class and Description |
---|---|
class |
Clustering<M extends Model>
Result class for clusterings.
|
Modifier and Type | Class and Description |
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static class |
EvaluateClustering.ScoreResult
Result object for outlier score judgements.
|
Modifier and Type | Class and Description |
---|---|
class |
Segments
Creates segments of two or more clusterings.
|
Modifier and Type | Class and Description |
---|---|
class |
IndexStatistics.IndexMetaResult
Result class.
|
Modifier and Type | Class and Description |
---|---|
class |
JudgeOutlierScores.ScoreResult
Result object for outlier score judgements.
|
Modifier and Type | Class and Description |
---|---|
class |
AprioriResult
Result class for Apriori Algorithm.
|
class |
CollectionResult<O>
Simple 'collection' type of result.
|
class |
HistogramResult<O>
Histogram result.
|
class |
KNNDistanceOrderResult<D extends Distance<D>>
Wraps a list containing the knn distances.
|
class |
OrderingFromDataStore<T extends Comparable<T>>
Result class providing an ordering backed by a hashmap.
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class |
ReferencePointsResult<O>
Result used in passing the reference points to the visualizers.
|
class |
ScalesResult
Class to keep shared scales across visualizers.
|
class |
SettingsResult
Result that keeps track of settings that were used in generating this
particular result.
|
Modifier and Type | Class and Description |
---|---|
class |
ClusterOrderResult<D extends Distance<D>>
Class to store the result of an ordering clustering algorithm such as OPTICS.
|
Modifier and Type | Class and Description |
---|---|
class |
OutlierResult
Wrap a typical Outlier result, keeping direct references to the main result
parts.
|
Modifier and Type | Class and Description |
---|---|
class |
SimpleParallel
Simple parallel projection
Scaled space: reordered, scaled and inverted.
|
Modifier and Type | Field and Description |
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private BasicResult |
AlgorithmStep.result
The algorithm output
|