| 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.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 | 
ExternalDoubleOutlierScore.scaling
Scaling function to use 
 | 
private ScalingFunction | 
ExternalDoubleOutlierScore.Parameterizer.scaling
Scaling function to use 
 | 
private ScalingFunction | 
RescaleMetaOutlierAlgorithm.scaling
Scaling function to use 
 | 
private ScalingFunction | 
RescaleMetaOutlierAlgorithm.Parameterizer.scaling
Scaling function to use 
 | 
| Constructor and Description | 
|---|
ExternalDoubleOutlierScore(java.io.File file,
                          java.util.regex.Pattern idpattern,
                          java.util.regex.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 | 
ComputeKNNOutlierScores.scaling
Scaling function. 
 | 
(package private) ScalingFunction | 
ComputeKNNOutlierScores.Parameterizer.scaling
Scaling function. 
 | 
(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. 
 | 
| 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(java.io.PrintStream out,
           DBIDs ids,
           OutlierResult result,
           ScalingFunction scaling,
           java.lang.String label)
Write a single output line. 
 | 
| Constructor and Description | 
|---|
ComputeKNNOutlierScores(InputStep inputstep,
                       DistanceFunction<? super O> distf,
                       IntGenerator krange,
                       ByLabelOutlier bylabel,
                       java.io.File outfile,
                       ScalingFunction scaling,
                       java.util.regex.Pattern disable,
                       int ksquarestop)
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 | 
|---|---|
(package private) ScalingFunction | 
OutlierThresholdClustering.scaling
Scaling function to use 
 | 
(package private) ScalingFunction | 
OutlierThresholdClustering.Parameterizer.scaling
Scaling function to use 
 | 
private ScalingFunction | 
ComputeOutlierHistogram.scaling
Scaling function to use 
 | 
protected ScalingFunction | 
ComputeOutlierHistogram.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 | 
|---|
ComputeOutlierHistogram(java.util.regex.Pattern positive_class_name,
                       int bins,
                       ScalingFunction scaling,
                       boolean splitfreq)
Constructor. 
 | 
JudgeOutlierScores(java.util.regex.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  | 
OutlierScaling
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
 
 Reference: 
H.  | 
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  | 
MixtureModelOutlierScaling
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 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 -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  | 
SigmoidOutlierScaling
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 © 2019 ELKI Development Team. License information.