def __init__(self, build_from_scratch=False):
if build_from_scratch or not MrtRecommendationDependencies.model_exists(
"ridership_model.sav"):
self.build_models()
else:
self._models = pickle.load(
open(
MrtRecommendationDependencies.get_model_path(
"ridership_model.sav"), "rb"))
def __init__(self, build_from_scratch=False):
if build_from_scratch or not MrtRecommendationDependencies.model_exists(
"trip_classifier.sav"):
self.init_model()
X, Y = self.init_training_data()
self.train_model(X, Y)
else:
self._model = pickle.load(
open(
MrtRecommendationDependencies.get_model_path(
"trip_classifier.sav"), "rb"))
def __init__(self, field='num_train_running', build_from_scratch=False):
self._field = field
if build_from_scratch or not MrtRecommendationDependencies.model_exists(
f"{field}_model.sav"):
self.init_training_data()
self.init_model()
self.train_model()
else:
self._model = pickle.load(
open(
MrtRecommendationDependencies.get_model_path(
f"{self._field}_model.sav"), "rb"))
def dump_model(self):
pickle.dump(
self._models,
open(
MrtRecommendationDependencies.get_model_path(
"ridership_model.sav"), "wb"))
def dump_model(self):
pickle.dump(
self._model,
open(
MrtRecommendationDependencies.get_model_path(
"trip_classifier.sav"), "wb"))
def dump_model(self):
pickle.dump(
self._model,
open(
MrtRecommendationDependencies.get_model_path(
f"{self._field}_model.sav"), "wb"))