POSEvaluator evaluator = new POSEvaluator( new opennlp.tools.postag.POSTaggerME(model), missclassifiedListener, reportListener); evaluator.evaluate(sampleStream); System.out.println("Accuracy: " + evaluator.getWordAccuracy());
params, this.factory); POSEvaluator evaluator = new POSEvaluator(new POSTaggerME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); wordAccuracy.add(evaluator.getWordAccuracy(), evaluator.getWordCount());
@Test public void testPositive() throws InvalidFormatException { OutputStream stream = new ByteArrayOutputStream(); POSTaggerEvaluationMonitor listener = new POSEvaluationErrorListener(stream); POSEvaluator eval = new POSEvaluator(new DummyPOSTagger( POSSampleTest.createGoldSample()), listener); eval.evaluateSample(POSSampleTest.createGoldSample()); Assert.assertEquals(1.0, eval.getWordAccuracy(), 0.0); Assert.assertEquals(0, stream.toString().length()); }
/** * Detail evaluation of a model, outputting the report a file. */ public final void detailEvaluate() { final List<EvaluationMonitor<POSSample>> listeners = new LinkedList<EvaluationMonitor<POSSample>>(); final POSTaggerFineGrainedReportListener detailedFListener = new POSTaggerFineGrainedReportListener( System.out); listeners.add(detailedFListener); final POSEvaluator evaluator = new POSEvaluator(this.posTagger, listeners.toArray(new POSTaggerEvaluationMonitor[listeners.size()])); try { evaluator.evaluate(this.testSamples); } catch (IOException e) { e.printStackTrace(); } detailedFListener.writeReport(); }
private void eval(POSModel model, File testData, double expectedAccuracy) throws IOException { ObjectStream<POSSample> samples = new ConllXPOSSampleStream( new MarkableFileInputStreamFactory(testData), StandardCharsets.UTF_8); POSEvaluator evaluator = new POSEvaluator(new POSTaggerME(model)); evaluator.evaluate(samples); Assert.assertEquals(expectedAccuracy, evaluator.getWordAccuracy(), 0.0001); }
params, this.factory); POSEvaluator evaluator = new POSEvaluator(new POSTaggerME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); wordAccuracy.add(evaluator.getWordAccuracy(), evaluator.getWordCount());
@Test public void testNegative() throws InvalidFormatException { OutputStream stream = new ByteArrayOutputStream(); POSTaggerEvaluationMonitor listener = new POSEvaluationErrorListener(stream); POSEvaluator eval = new POSEvaluator( new DummyPOSTagger(POSSampleTest.createGoldSample()), listener); eval.evaluateSample(POSSampleTest.createPredSample()); Assert.assertEquals(.7, eval.getWordAccuracy(), .1d); Assert.assertNotSame(0, stream.toString().length()); }
/** * Evaluate word accuracy. */ public final void evaluate() { final POSEvaluator evaluator = new POSEvaluator(this.posTagger); try { evaluator.evaluate(this.testSamples); } catch (IOException e) { e.printStackTrace(); } System.out.println(evaluator.getWordAccuracy()); }
params, this.factory); POSEvaluator evaluator = new POSEvaluator(new POSTaggerME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); wordAccuracy.add(evaluator.getWordAccuracy(), evaluator.getWordCount());
/** * Evaluate and print every error. */ public final void evalError() { final List<EvaluationMonitor<POSSample>> listeners = new LinkedList<EvaluationMonitor<POSSample>>(); listeners.add(new POSEvaluationErrorListener()); final POSEvaluator evaluator = new POSEvaluator(this.posTagger, listeners.toArray(new POSTaggerEvaluationMonitor[listeners.size()])); try { evaluator.evaluate(this.testSamples); } catch (IOException e) { e.printStackTrace(); } System.out.println(evaluator.getWordAccuracy()); }
public final POSModel train(final TrainingParameters params) { // features if (getPosTaggerFactory() == null) { throw new IllegalStateException( "Classes derived from AbstractTrainer must " + " create a POSTaggerFactory features!"); } // training model POSModel trainedModel = null; POSEvaluator posEvaluator = null; try { trainedModel = POSTaggerME.train(this.lang, this.trainSamples, params, getPosTaggerFactory()); final POSTaggerME posTagger = new POSTaggerME(trainedModel); posEvaluator = new POSEvaluator(posTagger); posEvaluator.evaluate(this.testSamples); } catch (final IOException e) { System.err.println("IO error while loading training and test sets!"); e.printStackTrace(); System.exit(1); } System.out.println("Final result: " + posEvaluator.getWordAccuracy()); return trainedModel; }
POSEvaluator evaluator = new POSEvaluator(tagger); evaluator.evaluate(stream); return evaluator.getWordAccuracy();
POSEvaluator evaluator = new POSEvaluator( new opennlp.tools.postag.POSTaggerME(model), missclassifiedListener, reportListener); evaluator.evaluate(sampleStream); System.out.println("Accuracy: " + evaluator.getWordAccuracy());
POSEvaluator evaluator = new POSEvaluator( new opennlp.tools.postag.POSTaggerME(model), missclassifiedListener, reportListener); evaluator.evaluate(sampleStream); System.out.println("Accuracy: " + evaluator.getWordAccuracy());