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See:
Description

| Interface Summary | |
|---|---|
| OutlierScalingFunction | Interface for scaling functions used by Outlier evaluation such as Histograms and visualization. |
| Class Summary | |
|---|---|
| HeDESNormalizationOutlierScaling | Normalization used by HeDES |
| 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 probability 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 |
| 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. |
Scaling of Outlier scores, that require a statistical analysis of the occurring values
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