Package elki.math.statistics.intrinsicdimensionality

Interface IntrinsicDimensionalityEstimator<O>

Type Parameters:

O - Input object type when not used with distances.

All Known Subinterfaces:

DistanceBasedIntrinsicDimensionalityEstimator

All Known Implementing Classes:

ABIDEstimator, AggregatedHillEstimator, ALIDEstimator, EnsembleEstimator, GEDEstimator, HillEstimator, LMomentsEstimator, LPCAEstimator, MOMEstimator, PWM2Estimator, PWMEstimator, RABIDEstimator, RVEstimator, TightLIDEstimator, ZipfEstimator

public interface IntrinsicDimensionalityEstimator<O>

Estimate the intrinsic dimensionality from a distance list.

Since:

0.7.0

Author:

Erich Schubert

Method Summary

Modifier and Type	Method	Description
double	estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<? extends O> distq, DBIDRef cur, int k)	Estimate from a Reference Point, a KNNSearcher and the neighborhood size k.
double	estimate(RangeSearcher<DBIDRef> rnq, DistanceQuery<? extends O> distq, DBIDRef cur, double range)	Estimate from a distance list.

Method Detail

estimate

double estimate(KNNSearcher<DBIDRef> knnq,
                DistanceQuery<? extends O> distq,
                DBIDRef cur,
                int k)

Estimate from a Reference Point, a KNNSearcher and the neighborhood size k.

Parameters:

knnq - KNNSearcher

distq - Distance query for additional distances

cur - reference point

k - neighborhood size

Returns:

Estimated intrinsic dimensionality

estimate

double estimate(RangeSearcher<DBIDRef> rnq,
                DistanceQuery<? extends O> distq,
                DBIDRef cur,
                double range)

Estimate from a distance list.

Parameters:

rnq - RangeSearcher

distq - Distance query for additional distances

cur - reference point

range - neighborhood radius

Returns:

Estimated intrinsic dimensionality