public boolean buildingModelTree() { return !regressionTreeOption.isSet(); }
public RandomRBFGeneratorEvents() { noiseInClusterOption.set(); // eventDeleteCreateOption.set(); // eventMergeSplitOption.set(); }
protected void setMeasures(boolean[] measures) { this.generalEvalOption.setValue(measures[0]); this.f1Option.setValue(measures[1]); this.entropyOption.setValue(measures[2]); this.cmmOption.setValue(measures[3]); this.ssqOption.setValue(measures[4]); this.separationOption.setValue(measures[5]); this.silhouetteOption.setValue(measures[6]); this.statisticalOption.setValue(measures[7]); }
FlagOption suppressStatusOutOpt = new FlagOption("suppressStatusOut", 'S', SUPPRESS_STATUS_OUT_MSG); FlagOption suppressResultOutOpt = new FlagOption("suppressResultOut", 'R', SUPPRESS_RESULT_OUT_MSG);
FlagOption suppressStatusOutputOption = new FlagOption( "suppressStatusOutput", 'S', "Suppress the task status output that is normally send to stderr."); FlagOption suppressResultOutputOption = new FlagOption( "suppressResultOutput", 'R', "Suppress the task result output that is normally send to stdout."); if (suppressStatusOutputOption.isSet()) { result = task.doTask(); } else { ((FailedTaskReport) result).getFailureReason().printStackTrace(); } else { if (!suppressResultOutputOption.isSet()) { if (result instanceof Measurement[]) { StringBuilder sb = new StringBuilder();
public FlagOptionEditComponent(Option opt) { FlagOption option = (FlagOption) opt; this.editedOption = option; setEditState(this.editedOption.getValueAsCLIString()); }
FlagOption suppressStatusOutOpt = new FlagOption("suppressStatusOut", 'S', SUPPRESS_STATUS_OUT_MSG); FlagOption suppressResultOutOpt = new FlagOption("suppressResultOut", 'R', SUPPRESS_RESULT_OUT_MSG);
public boolean buildingModelTree() { return !regressionTreeOption.isSet(); }
public AbstractClusterer() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the Clusterer.", 1); } if( implementsMicroClusterer()){ this.evaluateMicroClusteringOption = new FlagOption("evaluateMicroClustering", 'M', "Evaluate the underlying microclustering instead of the macro clustering"); } }
public RandomRBFGeneratorEvents() { noiseInClusterOption.set(); // eventDeleteCreateOption.set(); // eventMergeSplitOption.set(); }
public void set() { setValue(true); }
public boolean normalize() { return !doNotNormalizeOption.isSet(); }
public AbstractClusterer() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the Clusterer.", 1); } if (implementsMicroClusterer()) { this.evaluateMicroClusteringOption = new FlagOption("evaluateMicroClustering", 'M', "Evaluate the underlying microclustering instead of the macro clustering"); } }
public RandomRBFGeneratorEvents() { noiseInClusterOption.set(); // eventDeleteCreateOption.set(); // eventMergeSplitOption.set(); }
public void set() { setValue(true); }
@Override public void getModelDescription(StringBuilder out, int indent) { if(this.anomalyDetectionOption.isSet()){ if(this.Supervised.isSet()){ this.printAnomaliesSupervised(out, indent); // Get Model Description (Supervised method) }else if(this.Unsupervised.isSet()){ this.printAnomaliesUnsupervised(out, indent); // Get Model Description (Unsupervised method) } }else{ this.getModelDescriptionNoAnomalyDetection(out, indent); // Get Model Description no Anomaly detection } }
public AbstractClusterer() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the Clusterer.", 1); } if( implementsMicroClusterer()){ this.evaluateMicroClusteringOption = new FlagOption("evaluateMicroClustering", 'M', "Evaluate the underlying microclustering instead of the macro clustering"); } }
public RandomRBFGeneratorEvents() { noiseInClusterOption.set(); // eventDeleteCreateOption.set(); // eventMergeSplitOption.set(); }
public void unset() { setValue(false); }
@Override protected Object doMainTask(TaskMonitor monitor, ObjectRepository repository) { // Create an array to summarize the selected measures boolean[] measureCollection = new boolean[8]; measureCollection[0] = this.generalEvalOption.isSet(); measureCollection[1] = this.f1Option.isSet(); measureCollection[2] = this.entropyOption.isSet(); measureCollection[3] = this.cmmOption.isSet(); measureCollection[4] = this.ssqOption.isSet(); measureCollection[5] = this.separationOption.isSet(); measureCollection[6] = this.silhouetteOption.isSet(); measureCollection[7] = this.statisticalOption.isSet(); BatchCmd.runBatch((ClusteringStream) getPreparedClassOption(this.streamOption), (AbstractClusterer) getPreparedClassOption(this.learnerOption), measureCollection, (int) this.instanceLimitOption.getValue(), (String) dumpFileOption.getValue()); LearningCurve learningCurve = new LearningCurve("EvaluateClustering does not support custom output file (> [filename]).\n" + "Check out the dump file to see the results (if you haven't specified, dumpClustering.csv by default)."); //System.out.println(learner.toString()); return learningCurve; } }