OutlierScaling (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

All Superinterfaces:

elki.utilities.scaling.ScalingFunction

All Known Implementing Classes:

COPOutlierScaling, HeDESNormalizationOutlierScaling, LogRankingPseudoOutlierScaling, MinusLogGammaScaling, MinusLogStandardDeviationScaling, MixtureModelOutlierScaling, MultiplicativeInverseScaling, OutlierGammaScaling, OutlierLinearScaling, OutlierMinusLogScaling, OutlierSqrtScaling, RankingPseudoOutlierScaling, SigmoidOutlierScaling, SqrtStandardDeviationScaling, StandardDeviationScaling, TopKOutlierScaling
```
public interface OutlierScaling
extends elki.utilities.scaling.ScalingFunction
```
Interface for scaling functions used by Outlier evaluation such as Histograms and visualization. Make sure to invoke prepare(elki.result.outlier.OutlierResult) prior to applying the scaling function.

Since:

0.3

Author:

Erich Schubert

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`<A> void`	`prepare(A array, elki.utilities.datastructures.arraylike.NumberArrayAdapter<?,A> adapter)`	Prepare is called once for each data set, before getScaled() will be called.
`void`	`prepare(OutlierResult or)`	Prepare is called once for each data set, before getScaled() will be called.

Methods inherited from interface elki.utilities.scaling.ScalingFunction
getMax, getMin, getScaled

- Method Detail
  - prepare
```
void prepare(OutlierResult or)
```
    Prepare is called once for each data set, before getScaled() will be called. This function can be used to extract global parameters such as means, minimums or maximums from the outlier scores.
    
    Parameters:
    
    or - Outlier result to use
  - prepare
```
<A> void prepare(A array,
                 elki.utilities.datastructures.arraylike.NumberArrayAdapter<?,A> adapter)
```
    Prepare is called once for each data set, before getScaled() will be called. This function can be used to extract global parameters such as means, minimums or maximums from the score array. The method using a full OutlierResult is preferred, as it will allow access to the metadata.
    
    Parameters:
    
    array - Data to process
    
    adapter - Array adapter