@Override public int totalOutcomes() { return data.numClasses(); }
@Override public int totalOutcomes() { return data.numClasses(); }
@Override public int numClasses() { return super.numClasses(); }
private static int countClasses(final File classifier) throws IOException, ClassNotFoundException { final InputStream is = new FileInputStream( classifier ); final ObjectInputStream objectInputStream = new ObjectInputStream(is); final AbstractClassifier abstractClassifier = (AbstractClassifier) objectInputStream.readObject(); final Instances header = (Instances) objectInputStream.readObject(); objectInputStream.close(); return header.numClasses(); }
@Override public int numClasses() { return dataset().numClasses(); }
@Override public List<String> getLabels() { return IntStream.range(0, data.numClasses()) .boxed() .map(i -> data.classAttribute().value(i)) .collect(Collectors.toList()); }
@Override public LabeledSentenceProvider getSentenceProvider(Instances data) { List<File> files = new ArrayList<>(); List<String> labels = new ArrayList<>(); final int clsIdx = data.classIndex(); for (Instance inst : data) { labels.add(String.valueOf(inst.value(clsIdx))); final String path = inst.stringValue(1 - clsIdx); final File file = Paths.get(textsLocation.getAbsolutePath(), path).toFile(); files.add(file); } return new FileLabeledSentenceProvider(files, labels, data.numClasses()); }
@Override public LabeledSentenceProvider getSentenceProvider(Instances data) { List<File> files = new ArrayList<>(); List<String> labels = new ArrayList<>(); final int clsIdx = data.classIndex(); for (Instance inst : data) { labels.add(String.valueOf(inst.value(clsIdx))); final String path = inst.stringValue(1 - clsIdx); final File file = Paths.get(textsLocation.getAbsolutePath(), path).toFile(); files.add(file); } return new FileLabeledSentenceProvider(files, labels, data.numClasses()); }
/** * Initializes the m_Attributes of the class. */ private void init() { try { m_NumInstances = m_TrainSet.numInstances(); m_NumClasses = m_TrainSet.numClasses(); m_NumAttributes = m_TrainSet.numAttributes(); m_ClassType = m_TrainSet.classAttribute().type(); } catch (Exception e) { e.printStackTrace(); } }
/** * Initializes the m_Attributes of the class. */ private void init() { try { m_NumInstances = m_TrainSet.numInstances(); m_NumClasses = m_TrainSet.numClasses(); m_NumAttributes = m_TrainSet.numAttributes(); m_ClassType = m_TrainSet.classAttribute().type(); } catch (Exception e) { e.printStackTrace(); } }
/** * Initializes the m_Attributes of the class. */ private void init_m_Attributes() { try { m_NumInstances = m_Train.numInstances(); m_NumClasses = m_Train.numClasses(); m_NumAttributes = m_Train.numAttributes(); m_ClassType = m_Train.classAttribute().type(); m_InitFlag = ON; } catch(Exception e) { e.printStackTrace(); } }
/** * Initializes the m_Attributes of the class. */ private void init() { try { m_NumInstances = m_TrainSet.numInstances(); m_NumClasses = m_TrainSet.numClasses(); m_NumAttributes = m_TrainSet.numAttributes(); m_ClassType = m_TrainSet.classAttribute().type(); } catch (Exception e) { e.printStackTrace(); } }
/** * Initializes the m_Attributes of the class. */ private void init() { try { m_NumInstances = m_TrainSet.numInstances(); m_NumClasses = m_TrainSet.numClasses(); m_NumAttributes = m_TrainSet.numAttributes(); m_ClassType = m_TrainSet.classAttribute().type(); } catch (Exception e) { e.printStackTrace(); } }
/** * Initializes the m_Attributes of the class. */ private void init_m_Attributes() { try { m_NumInstances = m_Train.numInstances(); m_NumClasses = m_Train.numClasses(); m_NumAttributes = m_Train.numAttributes(); m_ClassType = m_Train.classAttribute().type(); m_InitFlag = ON; } catch(Exception e) { e.printStackTrace(); } }
public void testNominal() { m_Filter = getFilter(); m_Instances.setClassIndex(1); Instances result = useFilter(); // classes must be still the same assertEquals(m_Instances.numClasses(), result.numClasses()); // at least one cluster per label besides class assertTrue(result.numAttributes() >= m_Instances.numClasses() + 1); }
public void testNominal() { m_Filter = getFilter(); m_Instances.setClassIndex(1); Instances result = useFilter(); // classes must be still the same assertEquals(m_Instances.numClasses(), result.numClasses()); // at least one cluster per label besides class assertTrue(result.numAttributes() >= m_Instances.numClasses() + 1); }
/** * bag class for getting the result of the loaded classifier */ private static class LoadedClassifier { private AbstractClassifier newClassifier = null; private Instances newHeader = null; }
/** * bag class for getting the result of the loaded classifier */ private static class LoadedClassifier { private AbstractClassifier newClassifier = null; private Instances newHeader = null; }
public void testNominal() { m_Filter = getFilter(); m_Instances.setClassIndex(0); Instances result = useFilter(); // classes must be still the same assertEquals(m_Instances.numClasses(), result.numClasses()); // at least one attribute besides class assertTrue(result.numAttributes() >= 1 + 1); }
public void testNominal() { m_Filter = getFilter(); m_Instances.setClassIndex(0); Instances result = useFilter(); // classes must be still the same assertEquals(m_Instances.numClasses(), result.numClasses()); // at least one attribute besides class assertTrue(result.numAttributes() >= 1 + 1); }