
@Reference(authors="J. Gao, P.-N. Tan", title="Converting Output Scores from Outlier Detection Algorithms into Probability Estimates", booktitle="Proc. Sixth International Conference on Data Mining, 2006. ICDM\'06.", url="http://dx.doi.org/10.1109/ICDM.2006.43") public class MixtureModelOutlierScalingFunction extends Object implements OutlierScalingFunction
| Modifier and Type | Field and Description | 
|---|---|
| protected double | alphaMixing parameter alpha | 
| private static double | DELTAConvergence parameter | 
| protected double | lambdaParameter lambda of the exponential distribution (inliers) | 
| private static Logging | LOGThe logger for this class. | 
| protected double | muParameter mu of the gaussian distribution (outliers) | 
| static double | ONEBYSQRT2PIPrecomputed static value | 
| protected double | sigmaParameter sigma of the gaussian distribution (outliers) | 
| Constructor and Description | 
|---|
| MixtureModelOutlierScalingFunction() | 
| Modifier and Type | Method and Description | 
|---|---|
| protected static double | calcP_i(double f,
       double mu,
       double sigma)Compute p_i (Gaussian distribution, outliers) | 
| protected static double | calcPosterior(double f,
             double alpha,
             double mu,
             double sigma,
             double lambda)Compute the a posterior probability for the given parameters. | 
| protected static double | calcQ_i(double f,
       double lambda)Compute q_i (Exponential distribution, inliers) | 
| double | getMax()Get maximum resulting value. | 
| double | getMin()Get minimum resulting value. | 
| 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. | 
private static final Logging LOG
protected double mu
protected double sigma
protected double lambda
protected double alpha
public static final double ONEBYSQRT2PI
private static final double DELTA
protected static double calcP_i(double f,
             double mu,
             double sigma)
f - valuemu - Mu parametersigma - Sigma parameterprotected static double calcQ_i(double f,
             double lambda)
f - valuelambda - Lambda parameterprotected static double calcPosterior(double f,
                   double alpha,
                   double mu,
                   double sigma,
                   double lambda)
f - valuealpha - Alpha (mixing) parametermu - Mu (for gaussian)sigma - Sigma (for gaussian)lambda - Lambda (for exponential)public void prepare(OutlierResult or)
OutlierScalingFunctionprepare in interface OutlierScalingFunctionor - Outlier result to usepublic double getMax()
ScalingFunctionDouble.NaN or
 Double.POSITIVE_INFINITY.getMax in interface ScalingFunctionpublic double getMin()
ScalingFunctionDouble.NaN or
 Double.NEGATIVE_INFINITY.getMin in interface ScalingFunctionpublic double getScaled(double value)
ScalingFunctiongetScaled in interface ScalingFunctionvalue - Original value