def measure_time(data):
start = time.time()
system = System(data)
system.use_all_features()
system.use_feature_selection()
system.create_features()
system.train()
system.save_classifiers()
system.eval()
system.create_confidence_scores()
system.apply_global_model()
end = time.time()
return end-start
from Data import Data from System import System data = Data() system = System(data) # Create features and apply feature selection system.use_all_features() system.use_feature_selection() system.create_features() # Train classifiers and save them to pickle file system.train() system.save_classifiers() # Run pairwise classification event_event, event_timex = system.eval() print "Event-Event:" print event_event print "Event-Timex:" print event_timex # Run global model system.create_confidence_scores() system.apply_global_model() event_event, event_timex = system.eval_global_model() print "Event-Event:" print event_event print "Event-Timex:" print event_timex
class Distance:
def __init__(self):
self.data = Data()
self.system = System(self.data)
self.system.use_all_features()
self.system.use_feature_selection()
self.system.create_features()
self.system.train()
self.system.save_predictions_to_relations()
self.relations = self._get_relations()
same_sentence, not_same_sentence = self._sort_relations_after_in_same_sentence()
print "Same sentence event-event:"
truth, predicted = self._get_truth_and_prediction(same_sentence)
print Result(truth, predicted)
print "Same sentence event-timex:"
truth, predicted = self._get_truth_and_prediction(same_sentence, event_event=False)
print Result(truth, predicted)
print "Not same sentence event-event:"
truth, predicted = self._get_truth_and_prediction(not_same_sentence)
print Result(truth, predicted)
print "Not same sentence event-timex:"
truth, predicted = self._get_truth_and_prediction(not_same_sentence, event_event=False)
print Result(truth, predicted)
def _get_truth_and_prediction(self, rels, event_event=True):
prediction = []
truth = []
for rel in rels:
if event_event and rel.is_event_event():
prediction.append(rel.predicted_class)
truth.append(rel.relation_type)
elif not event_event and rel.is_event_timex():
prediction.append(rel.predicted_class)
truth.append(rel.relation_type)
return truth, prediction
def _get_relations(self):
rels = []
for text_obj in self.data.test.text_objects:
for relation in text_obj.relations:
if relation.is_event_event():
rels.append(relation)
elif relation.is_event_timex():
rels.append(relation)
return rels
def _sort_relations_after_in_same_sentence(self):
same_sentence = []
not_same_sentence = []
for rel in self.relations:
if rel.source.sentence == rel.target.sentence:
same_sentence.append(rel)
else:
not_same_sentence.append(rel)
return (same_sentence, not_same_sentence)
