@Test public void testReadModel() throws Exception { SentenceSplitter sentenceSplitter = new SentenceSplitter(); sentenceSplitter.readModel(new File(FILENAME_MODEL)); assertNotNull(sentenceSplitter.model); }
public void readModel(File file) throws IOException, FileNotFoundException, ClassNotFoundException { readModel(new FileInputStream(file)); }
SentenceSplitter { public void readModel(File file) throws IOException, FileNotFoundException, ClassNotFoundException { readModel(new FileInputStream(file)); } }
SentenceSplitter { public void readModel(File file) throws IOException, FileNotFoundException, ClassNotFoundException { readModel(new FileInputStream(file)); } SentenceSplitter(); }
SentenceSplitter { public void readModel(File file) throws IOException, FileNotFoundException, ClassNotFoundException { readModel(new FileInputStream(file)); } SentenceSplitter(); Instance makePredictionData(ArrayList<String> lines, Pipe myPipe); Instance makePredictionData(File predictFile, Pipe myPipe); InstanceList makePredictionData(File[] predictFiles, Pipe myPipe); InstanceList makeTrainingData(File[] trainFiles, boolean useTokenOffset, boolean splitUnitsAfterPunctuation); void train(InstanceList instList, Pipe dataPipe); List<Unit> predict(List<String> lines, String postprocessingFilter); List<Unit> predict(Instance inst, String filterName); ArrayList<String> getLabelsFromLabelSequence(LabelSequence ls); void writeModel(String filename); void readModel(File file); void readModel(InputStream is); ArrayList<String> readFile(File myFile); CRF getModel(); }
SentenceSplitter { public void readModel(File file) throws IOException, FileNotFoundException, ClassNotFoundException { readModel(new FileInputStream(file)); } SentenceSplitter(); Instance makePredictionData(ArrayList<String> lines, Pipe myPipe); Instance makePredictionData(File predictFile, Pipe myPipe); InstanceList makePredictionData(File[] predictFiles, Pipe myPipe); InstanceList makeTrainingData(File[] trainFiles, boolean useTokenOffset, boolean splitUnitsAfterPunctuation); void train(InstanceList instList, Pipe dataPipe); List<Unit> predict(List<String> lines, String postprocessingFilter); List<Unit> predict(Instance inst, String filterName); ArrayList<String> getLabelsFromLabelSequence(LabelSequence ls); void writeModel(String filename); void readModel(File file); void readModel(InputStream is); ArrayList<String> readFile(File myFile); CRF getModel();  }