Package de.lmu.ifi.dbs.elki.utilities.scaling.outlier

Scaling of Outlier scores, that require a statistical analysis of the occurring values

See: Description

Interface Summary

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

Class Summary

Class	Description
COPOutlierScaling	CDF based outlier score scaling.
COPOutlierScaling.Parameterizer	Parameterization class.
HeDESNormalizationOutlierScaling	Normalization used by HeDES
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.
MixtureModelOutlierScalingFunction	Tries to fit a mixture model (exponential for inliers and gaussian for outliers) to the outlier score distribution.
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.
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 -1 * Math.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.
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.
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.

Package de.lmu.ifi.dbs.elki.utilities.scaling.outlier Description

Scaling of Outlier scores, that require a statistical analysis of the occurring values