new LanguageDetectorME(model), listeners.toArray(new LanguageDetectorEvaluationMonitor[listeners.size()]));
@Test public void testSupportedLanguages() { LanguageDetector ld = new LanguageDetectorME(this.model); String[] supportedLanguages = ld.getSupportedLanguages(); Assert.assertEquals(4, supportedLanguages.length); }
/** * Starts the evaluation. * * @param samples * the data to train and test * @param nFolds * number of folds * * @throws IOException */ public void evaluate(ObjectStream<LanguageSample> samples, int nFolds) throws IOException { CrossValidationPartitioner<LanguageSample> partitioner = new CrossValidationPartitioner<>(samples, nFolds); while (partitioner.hasNext()) { CrossValidationPartitioner.TrainingSampleStream<LanguageSample> trainingSampleStream = partitioner.next(); LanguageDetectorModel model = LanguageDetectorME.train( trainingSampleStream, params, factory); LanguageDetectorEvaluator evaluator = new LanguageDetectorEvaluator( new LanguageDetectorME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); documentAccuracy.add(evaluator.getAccuracy(), evaluator.getDocumentCount()); } }
@Test public void testPredictLanguage() { LanguageDetector ld = new LanguageDetectorME(this.model); Language language = ld.predictLanguage("Dove รจ meglio che giochi"); Assert.assertEquals("ita", language.getLang()); }
LanguageDetector langDetectME = new LanguageDetectorME(model);
@Test public void processSample() throws Exception { LanguageDetectorModel model = LanguageDetectorMETest.trainModel(); LanguageDetectorME langdetector = new LanguageDetectorME(model);
@Test public void testPredictLanguages() { LanguageDetector ld = new LanguageDetectorME(this.model); Language[] languages = ld.predictLanguages("estava em uma marcenaria na Rua Bruno"); Assert.assertEquals(4, languages.length); Assert.assertEquals("pob", languages[0].getLang()); Assert.assertEquals("ita", languages[1].getLang()); Assert.assertEquals("spa", languages[2].getLang()); Assert.assertEquals("fra", languages[3].getLang()); }
new LanguageDetectorME(model), listeners.toArray(new LanguageDetectorEvaluationMonitor[listeners.size()]));
new LanguageDetectorME(model), listeners.toArray(new LanguageDetectorEvaluationMonitor[listeners.size()]));
/** * Starts the evaluation. * * @param samples * the data to train and test * @param nFolds * number of folds * * @throws IOException */ public void evaluate(ObjectStream<LanguageSample> samples, int nFolds) throws IOException { CrossValidationPartitioner<LanguageSample> partitioner = new CrossValidationPartitioner<>(samples, nFolds); while (partitioner.hasNext()) { CrossValidationPartitioner.TrainingSampleStream<LanguageSample> trainingSampleStream = partitioner.next(); LanguageDetectorModel model = LanguageDetectorME.train( trainingSampleStream, params, factory); LanguageDetectorEvaluator evaluator = new LanguageDetectorEvaluator( new LanguageDetectorME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); documentAccuracy.add(evaluator.getAccuracy(), evaluator.getDocumentCount()); } }
/** * Starts the evaluation. * * @param samples * the data to train and test * @param nFolds * number of folds * * @throws IOException */ public void evaluate(ObjectStream<LanguageSample> samples, int nFolds) throws IOException { CrossValidationPartitioner<LanguageSample> partitioner = new CrossValidationPartitioner<>(samples, nFolds); while (partitioner.hasNext()) { CrossValidationPartitioner.TrainingSampleStream<LanguageSample> trainingSampleStream = partitioner.next(); LanguageDetectorModel model = LanguageDetectorME.train( trainingSampleStream, params, factory); LanguageDetectorEvaluator evaluator = new LanguageDetectorEvaluator( new LanguageDetectorME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); documentAccuracy.add(evaluator.getAccuracy(), evaluator.getDocumentCount()); } }
LanguageDetector langDetectME = new LanguageDetectorME(model);
LanguageDetector langDetectME = new LanguageDetectorME(model);