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
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))
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))
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
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
def features(self, parse):
return rule_features(parse)
