See: Description
| Interface | Description |
|---|---|
| OutlierScalingFunction |
Interface for scaling functions used by Outlier evaluation such as Histograms
and visualization.
|
| Class | Description |
|---|---|
| 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