de.lmu.ifi.dbs.elki.result.outlier

Interface OutlierScoreMeta

All Superinterfaces:

Result

All Known Implementing Classes:

BasicOutlierScoreMeta, InvertedOutlierScoreMeta, ProbabilisticOutlierScore, QuotientOutlierScoreMeta

public interface OutlierScoreMeta
extends Result

Generic meta information about the value range of an outlier score. All values can be Double.NaN if not specified by the algorithm or not computed (actual values). For theoretical values, it is explicitly allowed to return Double.NEGATIVE_INFINITY or Double.POSITIVE_INFINITY.

Method Summary

Methods

Modifier and Type	Method and 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.

Methods inherited from interface de.lmu.ifi.dbs.elki.result.Result

getLongName, getShortName

Method Detail

getActualMinimum

double getActualMinimum()

Get the actual minimum of the value range.

Returns:

minimum or Double.NaN

getActualMaximum

double getActualMaximum()

Get the actual maximum of the value range.

Returns:

maximum or Double.NaN

getTheoreticalMinimum

double getTheoreticalMinimum()

Get the theoretical minimum of the value range.

Returns:

theoretical minimum or Double.NaN

getTheoreticalMaximum

double getTheoreticalMaximum()

Get the theoretical maximum of the value range. This value may be Double.NEGATIVE_INFINITY or Double.NaN.

Returns:

theoretical maximum or Double.NaN

getTheoreticalBaseline

double getTheoreticalBaseline()

Get the theoretical baseline of the value range. It will be common to see Double.POSITIVE_INFINITY here.

Returns:

theoretical baseline or Double.NaN

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)