de.lmu.ifi.dbs.elki.index.projected

Class PINN<O extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.Factory<O,O>

de.lmu.ifi.dbs.elki.index.projected.PINN<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

IndexFactory<O>

@Title(value="PINN: Projection Indexed Nearest Neighbors")
 @Reference(title="Finding local anomalies in very high dimensional space",
           authors="T. de Vries, S. Chawla, M. E. Houle",
           booktitle="Proc. IEEE 10th International Conference on Data Mining (ICDM)",
           url="https://doi.org/10.1109/ICDM.2010.151",
           bibkey="DBLP:conf/icdm/VriesCH10")
public class PINN<O extends NumberVector>
extends ProjectedIndex.Factory<O,O>

Projection-Indexed nearest-neighbors (PINN) is an index to retrieve the nearest neighbors in high dimensional spaces by using a random projection based index.

Reference:

Finding local anomalies in very high dimensional space
T. de Vries, S. Chawla, M. E. Houle
In: Proc. IEEE 10th International Conference on Data Mining (ICDM)

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	PINN.Parameterizer<O extends NumberVector> Parameterization class.

Field Summary

Fields inherited from class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.Factory

inner, kmulti, materialize, norefine, proj

Constructor Summary

Constructors

Constructor and Description
PINN(IndexFactory<O> inner, int t, double s, double h, RandomFactory random) Constructor.

Method Summary

Methods inherited from class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.Factory

getInputTypeRestriction, instantiate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PINN

public PINN(IndexFactory<O> inner,
            int t,
            double s,
            double h,
            RandomFactory random)

Constructor.

Parameters:

inner - Inner index

t - Target dimensionality

s - Sparsity

h - Neighborhood size multiplicator

random - Random generator factory