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

Class VisualizePairwiseGainMatrix

java.lang.Object

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

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

@Reference(authors="Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel",
           title="On Evaluation of Outlier Rankings and Outlier Scores",
           booktitle="Proc. 12th SIAM Int. Conf. on Data Mining (SDM 2012)",
           url="https://doi.org/10.1137/1.9781611972825.90",
           bibkey="DBLP:conf/sdm/SchubertWZK12")
public class VisualizePairwiseGainMatrix
extends AbstractApplication

Class to load an outlier detection summary file, as produced by ComputeKNNOutlierScores, and compute a matrix with the pairwise gains. It will have one column / row obtained for each combination.

The gain is always computed in relation to the better of the two input methods. Green colors indicate the result has improved, red indicate it became worse.

Reference:

Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel
On Evaluation of Outlier Rankings and Outlier Scores
Proc. 12th SIAM Int. Conf. on Data Mining (SDM 2012)

Since:

0.5.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	VisualizePairwiseGainMatrix.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private InputStep	inputstep The data input part.
private static Logging	LOG Get static logger.
private ScalingFunction	prescaling Outlier scaling to apply during preprocessing.
private VisualizerParameterizer	vispar Parameterizer for visualizers.
private EnsembleVoting	voting Ensemble voting function.

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

REFERENCE, VERSION

Constructor Summary

Constructors

Constructor and Description
VisualizePairwiseGainMatrix(InputStep inputstep, ScalingFunction prescaling, EnsembleVoting voting, VisualizerParameterizer vispar) Constructor.

Method Summary

Modifier and Type	Method and Description
static void	main(java.lang.String[] args) Main method.
void	run() Runs the application.
private void	showVisualization(VisualizerContext context, SimilarityMatrixVisualizer factory, VisualizationTask task) Show a single visualization.

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

Get static logger.

inputstep

private InputStep inputstep

The data input part.

vispar

private VisualizerParameterizer vispar

Parameterizer for visualizers.

prescaling

private ScalingFunction prescaling

Outlier scaling to apply during preprocessing.

voting

private EnsembleVoting voting

Ensemble voting function.

Constructor Detail

VisualizePairwiseGainMatrix

public VisualizePairwiseGainMatrix(InputStep inputstep,
                                   ScalingFunction prescaling,
                                   EnsembleVoting voting,
                                   VisualizerParameterizer vispar)

Constructor.

Parameters:

inputstep - Input step

prescaling - Scaling function for input scores.

voting - Voting function

vispar - Visualizer parameterizer

Method Detail

run

public void run()

Description copied from class: AbstractApplication

Runs the application.

Specified by:

run in class AbstractApplication

showVisualization

private void showVisualization(VisualizerContext context,
                               SimilarityMatrixVisualizer factory,
                               VisualizationTask task)

Show a single visualization.

Parameters:

context - Visualizer context

factory - Visualizer factory

task - Visualization task

main

public static void main(java.lang.String[] args)

Main method.

Parameters:

args - Command line parameters.