de.lmu.ifi.dbs.elki.application.greedyensemble

Class ComputeKNNOutlierScores<O extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.application.AbstractApplication

de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores<O>

Type Parameters:

O - Vector type

@Reference(authors="E. Schubert, R. Wojdanowski, A. Zimek, H.-P. Kriegel",
           title="On Evaluation of Outlier Rankings and Outlier Scores",
           booktitle="Proc. 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, 2012.")
public class ComputeKNNOutlierScores<O extends NumberVector>
extends AbstractApplication

Application that runs a series of kNN-based algorithms on a data set, for building an ensemble in a second step. The output file consists of a label and one score value for each object. Since some algorithms can be too slow to run on large data sets and for large values of k, they can be disabled. For example -disable '(LDOF|FastABOD)' disables these two methods. For methods where k=1 does not make sense, this value will be skipped, and the procedure will commence at 1+stepsize. Reference:

E. Schubert, R. Wojdanowski, A. Zimek, H.-P. Kriegel
On Evaluation of Outlier Rankings and Outlier Scores
In Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, 2012.

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
private static interface	ComputeKNNOutlierScores.AlgRunner Run an algorithm for a given k.
static class	ComputeKNNOutlierScores.Parameterizer<O extends NumberVector> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
(package private) ByLabelOutlier	bylabel By label outlier detection - reference
(package private) Pattern	disable Pattern for disabling (skipping) methods.
(package private) DistanceFunction<? super O>	distf Distance function to use
(package private) InputStep	inputstep Input step
private static Logging	LOG Our logger class.
(package private) int	maxk Maximum value of k
(package private) File	outfile Output file
(package private) ScalingFunction	scaling Scaling function.
(package private) int	startk Starting value of k.
(package private) int	stepk k step size

Fields inherited from class de.lmu.ifi.dbs.elki.application.AbstractApplication

REFERENCE, VERSION

Constructor Summary

Constructors

Constructor and Description
ComputeKNNOutlierScores(InputStep inputstep, DistanceFunction<? super O> distf, int startk, int stepk, int maxk, ByLabelOutlier bylabel, File outfile, ScalingFunction scaling, Pattern disable) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected boolean	isDisabled(String name) Test if a given algorithm is disabled.
static void	main(String[] args) Main method.
void	run() Runs the application.
private void	runForEachK(String prefix, int startk, int stepk, int maxk, ComputeKNNOutlierScores.AlgRunner runner) Iterate over the k range.
(package private) void	writeResult(PrintStream out, DBIDs ids, OutlierResult result, ScalingFunction scaling, String label) Write a single output line.

Methods inherited from class de.lmu.ifi.dbs.elki.application.AbstractApplication

printErrorMessage, runCLIApplication, usage

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Our logger class.

inputstep

final InputStep inputstep

Input step

distf

final DistanceFunction<? super O extends NumberVector> distf

Distance function to use

startk

final int startk

Starting value of k.

stepk

final int stepk

k step size

maxk

final int maxk

Maximum value of k

outfile

File outfile

Output file

bylabel

ByLabelOutlier bylabel

By label outlier detection - reference

scaling

ScalingFunction scaling

Scaling function.

disable

Pattern disable

Pattern for disabling (skipping) methods.

Constructor Detail

ComputeKNNOutlierScores

public ComputeKNNOutlierScores(InputStep inputstep,
                       DistanceFunction<? super O> distf,
                       int startk,
                       int stepk,
                       int maxk,
                       ByLabelOutlier bylabel,
                       File outfile,
                       ScalingFunction scaling,
                       Pattern disable)

Constructor.

Parameters:

inputstep - Input step

distf - Distance function

startk - Starting value of k

stepk - K step size

maxk - Maximum k value

bylabel - By label outlier (reference)

outfile - Output file

scaling - Scaling function

disable - Pattern for disabling methods

Method Detail

run

public void run()

Description copied from class: AbstractApplication

Runs the application.

Specified by:

run in class AbstractApplication

writeResult

void writeResult(PrintStream out,
               DBIDs ids,
               OutlierResult result,
               ScalingFunction scaling,
               String label)

Write a single output line.

Parameters:

out - Output stream

ids - DBIDs

result - Outlier result

scaling - Scaling function

label - Identification label

runForEachK

private void runForEachK(String prefix,
               int startk,
               int stepk,
               int maxk,
               ComputeKNNOutlierScores.AlgRunner runner)

Iterate over the k range.

Parameters:

prefix - Prefix string

startk - Start k

stepk - Step k

maxk - Max k

runner - Runner to run

isDisabled

protected boolean isDisabled(String name)

Test if a given algorithm is disabled.

Parameters:

name - Algorithm name

Returns:

true if disabled

main

public static void main(String[] args)

Main method.

Parameters:

args - Command line parameters.