/** * Constructor. */ public MultiClassClassifier() { m_Classifier = new weka.classifiers.functions.Logistic(); }
/** * Constructor. */ public MultiClassClassifier() { m_Classifier = new weka.classifiers.functions.Logistic(); }
/** * Default (argument-less) constructor. Will initialize the instance with * a default Weka-classifier (here, that default is, NaiveBayes with Kernel density estimation) * * @throws ClassifierException */ public EDABinaryClassifierFromWeka() throws ClassifierException { this(new Logistic(), null); // logistic regression is generally go good in most situations. //this(new NaiveBayes(), new String[] {"-K"}); }
/** * Main method for testing this class. * * @param argv should contain the command line arguments to the scheme (see * Evaluation) */ public static void main(String[] argv) { runClassifier(new Logistic(), argv); }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
/** * Main method for testing this class. * * @param argv should contain the command line arguments to the scheme (see * Evaluation) */ public static void main(String[] argv) { runClassifier(new Logistic(), argv); }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
/** Creates a default Logistic */ public Classifier getClassifier() { return new Logistic(); }
/** Creates a default Logistic */ public Classifier getClassifier() { return new Logistic(); }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }
@Override protected EDAClassifierAbstraction prepareClassifier() throws EDAException { try { return new EDABinaryClassifierFromWeka(new Logistic(), null); // you can use other classifiers from Weka, such as ... //return new EDABinaryClassifierFromWeka(new NaiveBayes(), null); //return new EDABinaryClassifierFromWeka(new VotedPerceptron(), null); //return new EDABinaryClassifierFromWeka(new J48(), null); //return new EDABinaryClassifierFromWeka(new MultilayerPerceptron(), null); //return new EDABinaryClassifierFromWeka(new KStar(), null); //return new EDABinaryClassifierFromWeka(new SimpleLogistic(), null); //return new EDABinaryClassifierFromWeka(new RandomForest(), null); } catch (ClassifierException ce) { throw new EDAException("Preparing an instance of Classifier for EDA failed: underlying Classifier raised an exception: ", ce); } }