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"))