How to use

NaiveBayesModelWriter

in

opennlp.tools.ml.naivebayes

writeUTF("NaiveBayes");
writeInt(OUTCOME_LABELS.length);
 writeUTF(label);
ComparablePredicate[] sorted = sortValues();
List<List<ComparablePredicate>> compressed = computeOutcomePatterns(sorted);
writeInt(compressed.size());
 writeUTF(a.size() + a.get(0).toString());
writeInt(sorted.length);
 writeUTF(s.name);
  writeDouble(sorted[i].params[j]);
close();

protected static NaiveBayesModel persistedModel(NaiveBayesModel model) throws IOException {
 Path tempFilePath = Files.createTempFile("ptnb-", ".bin");
 File file = tempFilePath.toFile();
 try {
  NaiveBayesModelWriter modelWriter = new BinaryNaiveBayesModelWriter(model, file);
  modelWriter.persist();
  NaiveBayesModelReader reader = new BinaryNaiveBayesModelReader(file);
  reader.checkModelType();
  return (NaiveBayesModel)reader.constructModel();
 }
 finally {
  file.delete();
 }
}

@Test
public void testPlainTextModel() throws IOException {
 testDataIndexer.index(NaiveBayesCorrectnessTest.createTrainingStream());
 NaiveBayesModel model1 =
   (NaiveBayesModel) new NaiveBayesTrainer().trainModel(testDataIndexer);
 StringWriter sw1 = new StringWriter();
 NaiveBayesModelWriter modelWriter =
   new PlainTextNaiveBayesModelWriter(model1, new BufferedWriter(sw1));
 modelWriter.persist();
 NaiveBayesModelReader reader =
   new PlainTextNaiveBayesModelReader(new BufferedReader(new StringReader(sw1.toString())));
 reader.checkModelType();
 NaiveBayesModel model2 = (NaiveBayesModel)reader.constructModel();
 StringWriter sw2 = new StringWriter();
 modelWriter = new PlainTextNaiveBayesModelWriter(model2, new BufferedWriter(sw2));
 modelWriter.persist();
 System.out.println(sw1.toString());
 Assert.assertEquals(sw1.toString(), sw2.toString());
}

writeUTF("NaiveBayes");
writeInt(OUTCOME_LABELS.length);
 writeUTF(label);
ComparablePredicate[] sorted = sortValues();
List<List<ComparablePredicate>> compressed = computeOutcomePatterns(sorted);
writeInt(compressed.size());
 writeUTF(a.size() + a.get(0).toString());
writeInt(sorted.length);
 writeUTF(s.name);
  writeDouble(sorted[i].params[j]);
close();

@Test
public void testBinaryModelPersistence() throws Exception {
 testDataIndexer.index(NaiveBayesCorrectnessTest.createTrainingStream());
 NaiveBayesModel model = (NaiveBayesModel) new NaiveBayesTrainer().trainModel(testDataIndexer);
 Path tempFile = Files.createTempFile("bnb-", ".bin");
 File file = tempFile.toFile();
 try {
  NaiveBayesModelWriter modelWriter = new BinaryNaiveBayesModelWriter(model, file);
  modelWriter.persist();
  NaiveBayesModelReader reader = new BinaryNaiveBayesModelReader(file);
  reader.checkModelType();
  AbstractModel abstractModel = reader.constructModel();
  Assert.assertNotNull(abstractModel);
 }
 finally {
  file.delete();
 }
}

writeUTF("NaiveBayes");
writeInt(OUTCOME_LABELS.length);
 writeUTF(label);
ComparablePredicate[] sorted = sortValues();
List<List<ComparablePredicate>> compressed = computeOutcomePatterns(sorted);
writeInt(compressed.size());
 writeUTF(a.size() + a.get(0).toString());
writeInt(sorted.length);
 writeUTF(s.name);
  writeDouble(sorted[i].params[j]);
close();

 @Test
 public void testTextModelPersistence() throws Exception {
  testDataIndexer.index(NaiveBayesCorrectnessTest.createTrainingStream());
  NaiveBayesModel model = (NaiveBayesModel) new NaiveBayesTrainer().trainModel(testDataIndexer);
  Path tempFile = Files.createTempFile("ptnb-", ".txt");
  File file = tempFile.toFile();
  try {
   NaiveBayesModelWriter modelWriter = new PlainTextNaiveBayesModelWriter(model, file);
   modelWriter.persist();
   NaiveBayesModelReader reader = new PlainTextNaiveBayesModelReader(file);
   reader.checkModelType();
   AbstractModel abstractModel = reader.constructModel();
   Assert.assertNotNull(abstractModel);
  }
  finally {
   file.delete();
  }
 }
}