Package elki.result.outlier
Interface OutlierScoreMeta
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- All Known Implementing Classes:
BasicOutlierScoreMeta
,InvertedOutlierScoreMeta
,ProbabilisticOutlierScore
,QuotientOutlierScoreMeta
public interface OutlierScoreMeta
Generic meta information about the value range of an outlier score. All values can beDouble.NaN
if not specified by the algorithm or not computed (actual values). For theoretical values, it is explicitly allowed to returnDouble.NEGATIVE_INFINITY
orDouble.POSITIVE_INFINITY
.- Since:
- 0.3
- Author:
- Erich Schubert
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description double
getActualMaximum()
Get the actual maximum of the value range.double
getActualMinimum()
Get the actual minimum of the value range.double
getTheoreticalBaseline()
Get the theoretical baseline of the value range.double
getTheoreticalMaximum()
Get the theoretical maximum of the value range.double
getTheoreticalMinimum()
Get the theoretical minimum of the value range.double
normalizeScore(double value)
Return a normalized value of the outlier score.
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Method Detail
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getActualMinimum
double getActualMinimum()
Get the actual minimum of the value range.- Returns:
- minimum or
Double.NaN
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getActualMaximum
double getActualMaximum()
Get the actual maximum of the value range.- Returns:
- maximum or
Double.NaN
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getTheoreticalMinimum
double getTheoreticalMinimum()
Get the theoretical minimum of the value range.- Returns:
- theoretical minimum or
Double.NaN
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getTheoreticalMaximum
double getTheoreticalMaximum()
Get the theoretical maximum of the value range. This value may beDouble.NEGATIVE_INFINITY
orDouble.NaN
.- Returns:
- theoretical maximum or
Double.NaN
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getTheoreticalBaseline
double getTheoreticalBaseline()
Get the theoretical baseline of the value range. It will be common to seeDouble.POSITIVE_INFINITY
here.- Returns:
- theoretical baseline or
Double.NaN
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normalizeScore
double normalizeScore(double value)
Return a normalized value of the outlier score.- Parameters:
value
- outlier score- Returns:
- Normalized value (in 0.0-1.0)
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