Package de.lmu.ifi.dbs.elki.evaluation.outlier

Evaluate an outlier score using a misclassification based cost model

See: Description

Class Summary

Class	Description
ComputeOutlierHistogram	Compute a Histogram to evaluate a ranking algorithm.
ComputeOutlierHistogram.Parameterizer	Parameterization class.
JudgeOutlierScores	Compute a Histogram to evaluate a ranking algorithm.
JudgeOutlierScores.Parameterizer	Parameterization class.
OutlierPrecisionAtKCurve	Compute a curve containing the precision values for an outlier detection method.
OutlierPrecisionAtKCurve.Parameterizer	Parameterization class.
OutlierPrecisionAtKCurve.PrecisionAtKCurve	Precision at K curve.
OutlierPrecisionRecallCurve	Compute a curve containing the precision values for an outlier detection method.
OutlierPrecisionRecallCurve.Parameterizer	Parameterization class.
OutlierPrecisionRecallCurve.PRCurve	P/R Curve
OutlierRankingEvaluation	Evaluate outlier scores by their ranking
OutlierRankingEvaluation.Parameterizer	Parameterization class.
OutlierROCCurve	Compute a ROC curve to evaluate a ranking algorithm and compute the corresponding ROCAUC value.
OutlierROCCurve.Parameterizer	Parameterization class.
OutlierROCCurve.ROCResult	Result object for ROC curves.
OutlierSmROCCurve	Smooth ROC curves are a variation of classic ROC curves that takes the scores into account.
OutlierSmROCCurve.Parameterizer	Parameterization class.
OutlierSmROCCurve.SmROCResult	Result object for Smooth ROC curves.
OutlierThresholdClustering	Pseudo clustering algorithm that builds clusters based on their outlier score.
OutlierThresholdClustering.Parameterizer	Parameterization helper

Package de.lmu.ifi.dbs.elki.evaluation.outlier Description

Evaluate an outlier score using a misclassification based cost model