Beispiel #1
0
 def features(self, parse):
     features = defaultdict(float)
     # TODO: turning off rule features seems to screw up learning
     # figure out what's going on here
     # maybe make an exercise of it!
     # Actually it doesn't seem to mess up final result.
     # But the train accuracy reported during SGD is misleading?
     features.update(rule_features(parse))
     features.update(self.empty_denotation_feature(parse))
     # EXERCISE: Experiment with additional features.
     return features
Beispiel #2
0
def find_best_rules(domain):
    model = domain.model()
    examples = domain.train_examples()
    metric = domain.training_metric()
    rule_counts = defaultdict(int)
    for example in examples:
        parses = model.parse_input(example.input)
        good_parses = [p for p in parses if metric.evaluate(example, [p])]
        if good_parses:
            best_parse = good_parses[0]
            features = rule_features(best_parse)
            for rule, count in list(features.items()):
                rule_counts[rule] = rule_counts[rule] + count
    counts = [(count, rule) for rule, count in list(rule_counts.items())]
    counts = sorted(counts, reverse=True)
    for count, rule in counts:
        print('%d\t%s' % (count, rule))
Beispiel #3
0
def find_best_rules(domain):
    model = domain.model()
    examples = domain.train_examples()
    metric = domain.training_metric()
    rule_counts = defaultdict(int)
    for example in examples:
        parses = model.parse_input(example.input)
        good_parses = [p for p in parses if metric.evaluate(example, [p])]
        if good_parses:
            best_parse = good_parses[0]
            features = rule_features(best_parse)
            for rule, count in list(features.items()):
                rule_counts[rule] = rule_counts[rule] + count
    counts = [(count, rule) for rule, count in list(rule_counts.items())]
    counts = sorted(counts, reverse=True)
    for count, rule in counts:
        print('%d\t%s' % (count, rule))
Beispiel #4
0
 def features(self, parse):
     features = rule_features(parse)
     features.update(self.operator_precedence_features(parse))
     return features
Beispiel #5
0
 def features(self, parse):
     features = rule_features(parse)
     return features
Beispiel #6
0
 def features(self, parse):
     features = rule_features(parse)
     features.update(self.operator_precedence_features(parse))
     return features
 def features(self, parse):
     features = rule_features(parse)
     return features
Beispiel #8
0
 def features(self, parse):
     return rule_features(parse)