See: Description
Interface  Description 

OutlierScaling 
Interface for scaling functions used by Outlier evaluation such as Histograms
and visualization.

Class  Description 

COPOutlierScaling 
CDF based outlier score scaling.

COPOutlierScaling.Parameterizer 
Parameterization class.

HeDESNormalizationOutlierScaling 
Normalization used by HeDES
Reference:
H. 
LogRankingPseudoOutlierScaling 
This is a pseudo outlier scoring obtained by only considering the ranks of
the objects.

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.

MinusLogGammaScaling.Parameterizer 
Parameterization class.

MinusLogStandardDeviationScaling 
Scaling that can map arbitrary values to a probability in the range of [0:1].

MinusLogStandardDeviationScaling.Parameterizer 
Parameterization class.

MixtureModelOutlierScaling 
Tries to fit a mixture model (exponential for inliers and gaussian for
outliers) to the outlier score distribution.

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.

OutlierGammaScaling 
Scaling that can map arbitrary values to a probability in the range of [0:1]
by assuming a Gamma distribution on the values.

OutlierGammaScaling.Parameterizer 
Parameterization class.

OutlierLinearScaling 
Scaling that can map arbitrary values to a value in the range of [0:1].

OutlierLinearScaling.Parameterizer 
Parameterization 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. 
OutlierSqrtScaling 
Scaling that can map arbitrary positive values to a value in the range of
[0:1].

OutlierSqrtScaling.Parameterizer 
Parameterization class.

RankingPseudoOutlierScaling 
This is a pseudo outlier scoring obtained by only considering the ranks of
the objects.

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.

SqrtStandardDeviationScaling 
Scaling that can map arbitrary values to a probability in the range of [0:1].

SqrtStandardDeviationScaling.Parameterizer 
Parameterization class.

StandardDeviationScaling 
Scaling that can map arbitrary values to a probability in the range of [0:1].

StandardDeviationScaling.Parameterizer 
Parameterization class.

TopKOutlierScaling 
Outlier scaling function that only keeps the top k outliers.

TopKOutlierScaling.Parameterizer 
Parameterization class.

Copyright © 2019 ELKI Development Team. License information.