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