Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms.
|
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
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
Modifier and Type | Method and Description |
---|---|
CollectionResult<double[]> |
DistanceQuantileSampler.run(Database database,
Relation<O> rel)
Run the distance quantile sampler.
|
CollectionResult<double[]> |
AveragePrecisionAtK.run(Database database,
Relation<O> relation,
Relation<?> lrelation)
Run the algorithm
|
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 |
HistogramResult
Histogram result.
|
class |
ReferencePointsResult<O>
Result used in passing the reference points to the visualizers.
|
Modifier and Type | Method and Description |
---|---|
static java.util.List<CollectionResult<?>> |
ResultUtil.getCollectionResults(Result r)
Collect all collection results from a Result
|
Copyright © 2019 ELKI Development Team. License information.