Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.outlier.meta |
Meta outlier detection algorithms: external scores, score rescaling.
|
de.lmu.ifi.dbs.elki.application.greedyensemble |
Greedy ensembles for outlier detection.
|
de.lmu.ifi.dbs.elki.evaluation.histogram |
Functionality for the evaluation of algorithms using histograms.
|
de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix |
Render a distance matrix to visualize a clustering-distance-combination.
|
de.lmu.ifi.dbs.elki.utilities.scaling |
Scaling functions: linear, logarithmic, gamma, clipping, ...
|
de.lmu.ifi.dbs.elki.utilities.scaling.outlier |
Scaling of Outlier scores, that require a statistical analysis of the occurring values
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier |
Visualizers for outlier scores based on 2D projections.
|
Modifier and Type | Field and Description |
---|---|
private ScalingFunction |
RescaleMetaOutlierAlgorithm.scaling
Scaling function to use
|
private ScalingFunction |
RescaleMetaOutlierAlgorithm.Parameterizer.scaling
Scaling function to use
|
private ScalingFunction |
ExternalDoubleOutlierScore.scaling
Scaling function to use
|
private ScalingFunction |
ExternalDoubleOutlierScore.Parameterizer.scaling
Scaling function to use
|
Constructor and Description |
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ExternalDoubleOutlierScore(File file,
Pattern idpattern,
Pattern scorepattern,
boolean inverted,
ScalingFunction scaling)
Constructor.
|
RescaleMetaOutlierAlgorithm(Algorithm algorithm,
ScalingFunction scaling)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
(package private) ScalingFunction |
GreedyEnsembleExperiment.prescaling
Outlier scaling to apply during preprocessing.
|
(package private) ScalingFunction |
GreedyEnsembleExperiment.Parameterizer.prescaling
Outlier scaling to apply during preprocessing.
|
private ScalingFunction |
VisualizePairwiseGainMatrix.prescaling
Outlier scaling to apply during preprocessing.
|
private ScalingFunction |
VisualizePairwiseGainMatrix.Parameterizer.prescaling
Outlier scaling to apply during preprocessing.
|
(package private) ScalingFunction |
GreedyEnsembleExperiment.scaling
Outlier scaling to apply to constructed ensembles.
|
(package private) ScalingFunction |
GreedyEnsembleExperiment.Parameterizer.scaling
Outlier scaling to apply to constructed ensembles.
|
(package private) ScalingFunction |
ComputeKNNOutlierScores.scaling
Scaling function.
|
(package private) ScalingFunction |
ComputeKNNOutlierScores.Parameterizer.scaling
Scaling function.
|
Modifier and Type | Method and Description |
---|---|
static Relation<NumberVector> |
GreedyEnsembleExperiment.applyPrescaling(ScalingFunction scaling,
Relation<NumberVector> relation,
DBIDs skip)
Prescale each vector (except when in
skip ) with the given scaling
function. |
private static void |
GreedyEnsembleExperiment.applyScaling(double[] raw,
ScalingFunction scaling) |
(package private) void |
ComputeKNNOutlierScores.writeResult(PrintStream out,
DBIDs ids,
OutlierResult result,
ScalingFunction scaling,
String label)
Write a single output line.
|
Constructor and Description |
---|
ComputeKNNOutlierScores(InputStep inputstep,
DistanceFunction<? super O> distf,
int startk,
int stepk,
int maxk,
ByLabelOutlier bylabel,
File outfile,
ScalingFunction scaling,
Pattern disable)
Constructor.
|
GreedyEnsembleExperiment(InputStep inputstep,
EnsembleVoting voting,
GreedyEnsembleExperiment.Distance distance,
ScalingFunction prescaling,
ScalingFunction scaling,
double rate)
Constructor.
|
VisualizePairwiseGainMatrix(InputStep inputstep,
ScalingFunction prescaling,
EnsembleVoting voting,
VisualizerParameterizer vispar)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
private ScalingFunction |
ComputeOutlierHistogram.scaling
Scaling function to use
|
protected ScalingFunction |
ComputeOutlierHistogram.Parameterizer.scaling
Scaling function to use
|
Constructor and Description |
---|
ComputeOutlierHistogram(Pattern positive_class_name,
int bins,
ScalingFunction scaling,
boolean splitfreq)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
(package private) ScalingFunction |
OutlierThresholdClustering.scaling
Scaling function to use
|
(package private) ScalingFunction |
OutlierThresholdClustering.Parameterizer.scaling
Scaling function to use
|
private ScalingFunction |
JudgeOutlierScores.scaling
Scaling function to use
|
private ScalingFunction |
JudgeOutlierScores.Parameterizer.scaling
Scaling function to use
|
Constructor and Description |
---|
JudgeOutlierScores(Pattern positive_class_name,
ScalingFunction scaling)
Constructor.
|
OutlierThresholdClustering(ScalingFunction scaling,
double[] threshold)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
private ScalingFunction |
ComputeSimilarityMatrixImage.scaling
Scaling function to use
|
private ScalingFunction |
ComputeSimilarityMatrixImage.Parameterizer.scaling
Scaling function to use
|
Constructor and Description |
---|
ComputeSimilarityMatrixImage(DistanceFunction<? super O> distanceFunction,
ScalingFunction scaling,
boolean skipzero)
Constructor.
|
Modifier and Type | Interface and Description |
---|---|
interface |
StaticScalingFunction
Interface for Scaling functions that do NOT depend on analyzing the data set.
|
Modifier and Type | Class and Description |
---|---|
class |
ClipScaling
Scale implementing a simple clipping.
|
class |
GammaScaling
Non-linear scaling function using a Gamma curve.
|
class |
IdentityScaling
The trivial "identity" scaling function.
|
class |
LinearScaling
Simple linear scaling function.
|
class |
MinusLogScaling
Scaling function to invert values by computing -1 * Math.log(x)
|
Modifier and Type | Interface and Description |
---|---|
interface |
OutlierScalingFunction
Interface for scaling functions used by Outlier evaluation such as Histograms
and visualization.
|
Modifier and Type | Class and Description |
---|---|
class |
COPOutlierScaling
CDF based outlier score scaling.
|
class |
HeDESNormalizationOutlierScaling
Normalization used by HeDES
|
class |
LogRankingPseudoOutlierScaling
This is a pseudo outlier scoring obtained by only considering the ranks of
the objects.
|
class |
MinusLogGammaScaling
Scaling that can map arbitrary values to a probability in the range of [0:1],
by assuming a Gamma distribution on the data and evaluating the Gamma CDF.
|
class |
MinusLogStandardDeviationScaling
Scaling that can map arbitrary values to a probability in the range of [0:1].
|
class |
MixtureModelOutlierScalingFunction
Tries to fit a mixture model (exponential for inliers and gaussian for
outliers) to the outlier score distribution.
|
class |
MultiplicativeInverseScaling
Scaling function to invert values basically by computing 1/x, but in a variation
that maps the values to the [0:1] interval and avoiding division by 0.
|
class |
OutlierGammaScaling
Scaling that can map arbitrary values to a probability in the range of [0:1]
by assuming a Gamma distribution on the values.
|
class |
OutlierLinearScaling
Scaling that can map arbitrary values to a value in the range of [0:1].
|
class |
OutlierMinusLogScaling
Scaling function to invert values by computing -1 * Math.log(x)
Useful for example for scaling
ABOD , but see
MinusLogStandardDeviationScaling and MinusLogGammaScaling for
more advanced scalings for this algorithm. |
class |
OutlierSqrtScaling
Scaling that can map arbitrary positive values to a value in the range of
[0:1].
|
class |
RankingPseudoOutlierScaling
This is a pseudo outlier scoring obtained by only considering the ranks of
the objects.
|
class |
SigmoidOutlierScalingFunction
Tries to fit a sigmoid to the outlier scores and use it to convert the values
to probability estimates in the range of 0.0 to 1.0
Reference:
J.
|
class |
SqrtStandardDeviationScaling
Scaling that can map arbitrary values to a probability in the range of [0:1].
|
class |
StandardDeviationScaling
Scaling that can map arbitrary values to a probability in the range of [0:1].
|
class |
TopKOutlierScaling
Outlier scaling function that only keeps the top k outliers.
|
Modifier and Type | Field and Description |
---|---|
protected ScalingFunction |
BubbleVisualization.Parameterizer.scaling
Scaling function to use for Bubbles
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.