Package elki.application.greedyensemble
Class VisualizePairwiseGainMatrix
- java.lang.Object
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- elki.application.AbstractApplication
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- elki.application.greedyensemble.VisualizePairwiseGainMatrix
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@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 byComputeKNNOutlierScores
, 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
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
VisualizePairwiseGainMatrix.Par
Parameterization class.
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Field Summary
Fields Modifier and Type Field 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 elki.application.AbstractApplication
REFERENCE, VERSION
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Constructor Summary
Constructors Constructor Description VisualizePairwiseGainMatrix(InputStep inputstep, ScalingFunction prescaling, EnsembleVoting voting, VisualizerParameterizer vispar)
Constructor.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method 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 elki.application.AbstractApplication
printErrorMessage, runCLIApplication, usage
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Field Detail
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LOG
private static final Logging LOG
Get static logger.
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inputstep
private InputStep inputstep
The data input part.
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vispar
private VisualizerParameterizer vispar
Parameterizer for visualizers.
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prescaling
private ScalingFunction prescaling
Outlier scaling to apply during preprocessing.
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voting
private EnsembleVoting voting
Ensemble voting function.
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Constructor Detail
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VisualizePairwiseGainMatrix
public VisualizePairwiseGainMatrix(InputStep inputstep, ScalingFunction prescaling, EnsembleVoting voting, VisualizerParameterizer vispar)
Constructor.- Parameters:
inputstep
- Input stepprescaling
- Scaling function for input scores.voting
- Voting functionvispar
- Visualizer parameterizer
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Method Detail
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run
public void run()
Description copied from class:AbstractApplication
Runs the application.- Specified by:
run
in classAbstractApplication
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showVisualization
private void showVisualization(VisualizerContext context, SimilarityMatrixVisualizer factory, VisualizationTask task)
Show a single visualization.- Parameters:
context
- Visualizer contextfactory
- Visualizer factorytask
- Visualization task
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main
public static void main(java.lang.String[] args)
Main method.- Parameters:
args
- Command line parameters.
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