/** * Creates an classifier and setups the random seed option if the classifier is randomizable. */ public AbstractClassifier() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the classifier.", 1); } }
/** * Creates an classifier and setups the random seed option * if the classifier is randomizable. */ public AbstractClassifier() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the classifier.", 1); } }
/** * Creates an classifier and setups the random seed option if the classifier is randomizable. */ public AbstractClassifier() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the classifier.", 1); } }
/** * Creates an classifier and setups the random seed option * if the classifier is randomizable. */ public AbstractClassifier() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the classifier.", 1); } }
/** * Creates an classifier and setups the random seed option * if the classifier is randomizable. */ public AbstractClassifier() { if (isRandomizable()) { this.randomSeedOption = new IntOption("randomSeed", 'r', "Seed for random behaviour of the classifier.", 1); } }
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 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 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 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 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"); } }
IntOption statusUpdateFreqOpt = new IntOption("statusUpdateFrequency", 'F', STATUS_UPDATE_FREQ_MSG, 1000, 0, Integer.MAX_VALUE);
IntOption statusUpdateFreqOpt = new IntOption("statusUpdateFrequency", 'F', STATUS_UPDATE_FREQ_MSG, 1000, 0, Integer.MAX_VALUE);
attributes, 0); this.dataset.setClassIndex(this.numAttributes - 1); numAttsOption = new IntOption("numAtts", 'a', "", this.numAttributes);
"suppressResultOutput", 'R', "Suppress the task result output that is normally send to stdout."); IntOption statusUpdateFrequencyOption = new IntOption( "statusUpdateFrequency", 'F',
numAttsOption = new IntOption("numAtts", 'a',"", instances.numAttributes() - removeAttributes.length);