@Reference(authors="Hans-Peter Kriegel, Peer Kr\u00f6ger, Erich Schubert, Arthur Zimek", title="Interpreting and Unifying Outlier Scores", booktitle="Proc. 11th SIAM International Conference on Data Mining (SDM 2011)", url="https://doi.org/10.1137/1.9781611972818.2", bibkey="DBLP:conf/sdm/KriegelKSZ11") public class MinusLogStandardDeviationScaling extends StandardDeviationScaling
Transformation is done using the formula \(\max\{0, \mathrm{erf}(\lambda \frac{x-\mu}{\sigma\sqrt{2}})\}\)
Where mean can be fixed to a given value, and stddev is then computed against this mean.
Reference:
Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Interpreting and Unifying Outlier Scores
Proc. 11th SIAM International Conference on Data Mining (SDM 2011)
| Modifier and Type | Class and Description |
|---|---|
static class |
MinusLogStandardDeviationScaling.Parameterizer
Parameterization class.
|
factor, fixedmean, lambda, mean| Constructor and Description |
|---|
MinusLogStandardDeviationScaling(double fixedmean,
double lambda)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
double |
getScaled(double value)
Transform a given value using the scaling function.
|
void |
prepare(OutlierResult or)
Prepare is called once for each data set, before getScaled() will be
called.
|
getMax, getMin, preparepublic MinusLogStandardDeviationScaling(double fixedmean,
double lambda)
fixedmean - Fixed meanlambda - Scaling factor lambdapublic double getScaled(double value)
ScalingFunctiongetScaled in interface ScalingFunctiongetScaled in class StandardDeviationScalingvalue - Original valuepublic void prepare(OutlierResult or)
OutlierScalingprepare in interface OutlierScalingprepare in class StandardDeviationScalingor - Outlier result to useCopyright © 2019 ELKI Development Team. License information.