/** * Starts the evaluation. * * @param samples * the data to train and test * @param nFolds * number of folds * * @throws IOException */ public void evaluate(ObjectStream<DocumentSample> samples, int nFolds) throws IOException { CrossValidationPartitioner<DocumentSample> partitioner = new CrossValidationPartitioner<>( samples, nFolds); while (partitioner.hasNext()) { CrossValidationPartitioner.TrainingSampleStream<DocumentSample> trainingSampleStream = partitioner .next(); DoccatModel model = DocumentCategorizerME.train(languageCode, trainingSampleStream, params, factory); DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator( new DocumentCategorizerME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); documentAccuracy.add(evaluator.getAccuracy(), evaluator.getDocumentCount()); } }
DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator( new DocumentCategorizerME(model), listeners.toArray(new DoccatEvaluationMonitor[listeners.size()])); evaluator.evaluate(measuredSampleStream); } catch (IOException e) { System.err.println("failed");
DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator(doccat); evaluator.evaluate(stream); return evaluator.getAccuracy();
DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator( new DocumentCategorizerME(model), listeners.toArray(new DoccatEvaluationMonitor[listeners.size()])); evaluator.evaluate(measuredSampleStream); } catch (IOException e) { System.err.println("failed");
/** * Starts the evaluation. * * @param samples * the data to train and test * @param nFolds * number of folds * * @throws IOException */ public void evaluate(ObjectStream<DocumentSample> samples, int nFolds) throws IOException { CrossValidationPartitioner<DocumentSample> partitioner = new CrossValidationPartitioner<>( samples, nFolds); while (partitioner.hasNext()) { CrossValidationPartitioner.TrainingSampleStream<DocumentSample> trainingSampleStream = partitioner .next(); DoccatModel model = DocumentCategorizerME.train(languageCode, trainingSampleStream, params, factory); DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator( new DocumentCategorizerME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); documentAccuracy.add(evaluator.getAccuracy(), evaluator.getDocumentCount()); } }
DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator( new DocumentCategorizerME(model), listeners.toArray(new DoccatEvaluationMonitor[listeners.size()])); evaluator.evaluate(measuredSampleStream); } catch (IOException e) { System.err.println("failed");
/** * Starts the evaluation. * * @param samples * the data to train and test * @param nFolds * number of folds * * @throws IOException */ public void evaluate(ObjectStream<DocumentSample> samples, int nFolds) throws IOException { CrossValidationPartitioner<DocumentSample> partitioner = new CrossValidationPartitioner<>( samples, nFolds); while (partitioner.hasNext()) { CrossValidationPartitioner.TrainingSampleStream<DocumentSample> trainingSampleStream = partitioner .next(); DoccatModel model = DocumentCategorizerME.train(languageCode, trainingSampleStream, params, factory); DocumentCategorizerEvaluator evaluator = new DocumentCategorizerEvaluator( new DocumentCategorizerME(model), listeners); evaluator.evaluate(trainingSampleStream.getTestSampleStream()); documentAccuracy.add(evaluator.getAccuracy(), evaluator.getDocumentCount()); } }