Ejemplo n.º 1
0
    def test_predict(self):
        lines = sys.stdin.readlines()
        reader = IOBReader(lines)

        extractors = [
            FieldExtractor(reader.getPosition('FORM')), 
            FieldExtractor(reader.getPosition('POS')),
            CapitalExtractor(reader.getPosition('FORM')), 
        ]

        params = {'epochs':25, 'learning_rate':0.01, 'window_size':3, 'name_model':'model.ckpt'}
        classifier = Classifier(reader, extractors, LinearEstimator, **params)
        
        predicted = classifier.predict()
        #self.assertEqual(len(dataset), len(predicted))

        labels_idx_rev = {v:k for k,v in reader.vocabulary[reader.getPosition('LABEL')].items()}

        i = 0
        for line in lines:
            line = line.strip()
            if line:
                print '%s\t%s\t%s' % (line.split()[0], line.split()[1], labels_idx_rev[predicted[i]])
                i += 1
            else:
                print
Ejemplo n.º 2
0
    def test_train(self):
        f = {
            'fields': [
                {'position': 0, 'name': 'FORM', 'type': str},
                {'position': 1, 'name': 'POS', 'type': str},
                {'position': 2, 'name': 'LABEL', 'type': str}
            ]
        }
        
        reader = IOBReader(sys.stdin, separator='\t', format=f)
        extractors = [
            FieldExtractor(reader.getPosition('FORM')), 
            FieldExtractor(reader.getPosition('POS')),
            CapitalExtractor(reader.getPosition('FORM')), 
        ]

        params = {'epochs':25, 'learning_rate':0.01, 'window_size':3, 'name_model':'model.ckpt'}
        classifier = Classifier(reader, extractors, LinearEstimator, **params)
        classifier.train()