def _run_systems(self): for k in range(1, self.max_len+1): features = list(set(self._feature_series(k, self.features_event_event) + self._feature_series(k, self.features_event_timex))) print features data = Data() data.training = TrainingSet(False, False, "data/training/TBAQ-cleaned/TimeBank/") system = System(data, features) system.create_features() system.cross_validation() now = list(set(self._feature_series(k, self.features_event_event))) if k > 1: prev = list(set(self._feature_series(k-1, self.features_event_event))) if k > 1: if now != prev: self.accuracies_event_event.append(system.crossval_accuracy_event_event) print system.crossval_accuracy_event_event else: self.accuracies_event_event.append(system.crossval_accuracy_event_event) print system.crossval_accuracy_event_event now = list(set(self._feature_series(k, self.features_event_timex))) if k > 1: prev = list(set(self._feature_series(k-1, self.features_event_timex))) if k > 1: if now != prev: self.accuracies_event_timex.append(system.crossval_accuracy_event_timex) print system.crossval_accuracy_event_timex else: self.accuracies_event_timex.append(system.crossval_accuracy_event_timex) print system.crossval_accuracy_event_timex print
from Data import Data from System import System data = Data() system = System(data) system.use_best_feature_set() system.create_features() system.cross_validation() print system.crossval_accuracy_event_event print system.crossval_accuracy_event_timex