Package de.lmu.ifi.dbs.elki.result.outlier

Examples of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult

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    // setup Algorithm
    SOD<DoubleVector> sod = ClassGenericsUtil.parameterizeOrAbort(SOD.class, params);
    testParameterizationOk(params);

    // run SOD on database
    OutlierResult result = sod.run(db);

    testSingleScore(result, 1293, 1.7277777);
    testAUC(db, "Noise", result, 0.94956862);
  }
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    // setup Algorithm
    INFLO<DoubleVector, DoubleDistance> inflo = ClassGenericsUtil.parameterizeOrAbort(INFLO.class, params);
    testParameterizationOk(params);

    // run INFLO on database
    OutlierResult result = inflo.run(db);

    testSingleScore(result, 945, 2.5711647857619484);
    testAUC(db, "Noise", result, 0.935222);
  }
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    // setup Algorithm
    AggarwalYuNaive<DoubleVector> aggarwalYuNaive = ClassGenericsUtil.parameterizeOrAbort(AggarwalYuNaive.class, params);
    testParameterizationOk(params);

    // run AggarwalYuNaive on database
    OutlierResult result = aggarwalYuNaive.run(db);

    testSingleScore(result, 945, -2.3421601750764798);
    testAUC(db, "Noise", result, 0.8652037037037);
  }
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    // setup Algorithm
    LoOP<DoubleVector, DoubleDistance> loop = ClassGenericsUtil.parameterizeOrAbort(LoOP.class, params);
    testParameterizationOk(params);

    // run LoOP on database
    OutlierResult result = loop.run(db);

    testSingleScore(result, 945, 0.39805457858293325);
    testAUC(db, "Noise", result, 0.9443796296296296);
  }
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    // setup Algorithm
    ABOD<DoubleVector> abod = ClassGenericsUtil.parameterizeOrAbort(ABOD.class, params);
    testParameterizationOk(params);

    // run ABOD on database
    OutlierResult result = abod.run(db);

    testSingleScore(result, 945, 3.7108897864090475E-4);
    testAUC(db, "Noise", result, 0.9638148148148148);
  }
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    // setup Algorithm
    ReferenceBasedOutlierDetection<DoubleVector, DoubleDistance> referenceBasedOutlierDetection = ClassGenericsUtil.parameterizeOrAbort(ReferenceBasedOutlierDetection.class, params);
    testParameterizationOk(params);

    // run ReferenceBasedOutlierDetection on database
    OutlierResult result = referenceBasedOutlierDetection.run(db);

    testSingleScore(result, 945, 0.9260829537195538);
    testAUC(db, "Noise", result, 0.9892407407407409);
  }
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    // setup Algorithm
    GaussianModel<DoubleVector> gaussianModel = ClassGenericsUtil.parameterizeOrAbort(GaussianModel.class, params);
    testParameterizationOk(params);

    // run GaussianModel on database
    OutlierResult result = gaussianModel.run(db);

    testSingleScore(result, 1025, 2.8312466458765426);
    testAUC(db, "Noise", result, 0.9937641025641025);
  }
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    // setup Algorithm
    AggarwalYuEvolutionary<DoubleVector> aggarwalYuEvolutionary = ClassGenericsUtil.parameterizeOrAbort(AggarwalYuEvolutionary.class, params);
    testParameterizationOk(params);

    // run AggarwalYuEvolutionary on database
    OutlierResult result = aggarwalYuEvolutionary.run(db);

    testSingleScore(result, 945, 16.6553612449883);
    testAUC(db, "Noise", result, 0.5799537037037);
  }
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    // setup Algorithm
    LDOF<DoubleVector, DoubleDistance> ldof = ClassGenericsUtil.parameterizeOrAbort(LDOF.class, params);
    testParameterizationOk(params);

    // run LDOF on database
    OutlierResult result = ldof.run(db);

    testSingleScore(result, 1025, 0.8976268846182947);
    testAUC(db, "Noise", result, 0.9637948717948718);
  }
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    // setup Algorithm
    FeatureBagging fb = ClassGenericsUtil.parameterizeOrAbort(FeatureBagging.class, params);
    testParameterizationOk(params);

    // run AggarwalYuEvolutionary on database
    OutlierResult result = fb.run(db);

    testSingleScore(result, 1293, 11.8295414);
    testAUC(db, "Noise", result, 0.9066106);
  }
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Related Classes of de.lmu.ifi.dbs.elki.result.outlier.OutlierResult

  • de.lmu.ifi.dbs.elki.algorithm.outlier.ABOD
  • de.lmu.ifi.dbs.elki.algorithm.outlier.AbstractDBOutlier
  • de.lmu.ifi.dbs.elki.algorithm.outlier.AggarwalYuEvolutionary
  • de.lmu.ifi.dbs.elki.algorithm.outlier.AggarwalYuNaive
  • de.lmu.ifi.dbs.elki.algorithm.outlier.EMOutlier
  • de.lmu.ifi.dbs.elki.algorithm.outlier.GaussianModel
  • de.lmu.ifi.dbs.elki.algorithm.outlier.GaussianUniformMixture
  • de.lmu.ifi.dbs.elki.algorithm.outlier.INFLO
  • de.lmu.ifi.dbs.elki.algorithm.outlier.KNNOutlier
  • de.lmu.ifi.dbs.elki.algorithm.outlier.KNNWeightOutlier
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