ParallelKNNWeightOutlier (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- elki.outlier.distance.parallel.ParallelKNNWeightOutlier<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, OutlierAlgorithm
```
@Reference(authors="Erich Schubert, Arthur Zimek, Hans-Peter Kriegel",
           title="Local Outlier Detection Reconsidered: a Generalized View on Locality with Applications to Spatial, Video, and Network Outlier Detection",
           booktitle="Data Mining and Knowledge Discovery 28(1)",
           url="https://doi.org/10.1007/s10618-012-0300-z",
           bibkey="DBLP:journals/datamine/SchubertZK14")
public class ParallelKNNWeightOutlier<O>
extends java.lang.Object
implements OutlierAlgorithm
```
Parallel implementation of KNN Weight Outlier detection.
Reference:
F. Angiulli, C. Pizzuti
Fast Outlier Detection in High Dimensional Spaces
Proc. European Conf. Principles of Knowledge Discovery and Data Mining (PKDD'02)
This parallelized implementation is based on the easy-to-parallelize generalized pattern discussed in
Erich Schubert, Arthur Zimek, Hans-Peter Kriegel
Local Outlier Detection Reconsidered: a Generalized View on Locality with Applications to Spatial, Video, and Network Outlier Detection
Data Mining and Knowledge Discovery 28(1)

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary
- Nested classes/interfaces inherited from interface elki.Algorithm
  Algorithm.Utils

Field Summary

Fields
Modifier and Type Field Description

protected Distance<? super O> distance
Distance function used.

protected int kplus
Parameter k + 1

Constructor Summary

Constructors
Constructor Description

ParallelKNNWeightOutlier(Distance<? super O> distance, int k)
Constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`TypeInformation[]`	`getInputTypeRestriction()`	Get the input type restriction used for negotiating the data query.
`OutlierResult`	`run(Relation<O> relation)`	Run the parallel kNN weight outlier detector.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.outlier.OutlierAlgorithm
autorun

- Field Detail
  - distance
```
protected Distance<? super O> distance
```
    Distance function used.
  - kplus
```
protected int kplus
```
    Parameter k + 1
- Constructor Detail
  - ParallelKNNWeightOutlier
```
public ParallelKNNWeightOutlier(Distance<? super O> distance,
                                int k)
```
    Constructor.
    
    Parameters:
    
    distance - Distance function
    
    k - K parameter
- Method Detail
  - getInputTypeRestriction
```
public TypeInformation[] getInputTypeRestriction()
```
    Description copied from interface: Algorithm
    
    Get the input type restriction used for negotiating the data query.
    
    Specified by:
    
    getInputTypeRestriction in interface Algorithm
    
    Returns:
    
    Type restriction
  - run
```
public OutlierResult run(Relation<O> relation)
```
    Run the parallel kNN weight outlier detector.
    
    Parameters:
    
    relation - Relation to analyze
    
    Returns:
    
    Outlier detection result