def estimate(self): """Train the mini-models :return: the map of the trained models """ resource_data_list, impact_data_list = global_data_constructing_util.get_data( self.input_path, self.mini_model_map, self.model_results_path) return self._global_model_prediction(resource_data_list, impact_data_list)
def train(self): """Train the mini-models :return: the map of the trained models """ resource_data_list, impact_data_list = global_data_constructing_util.get_data( self.input_path, self.mini_model_map, self.model_results_path, self.warmup_period, self.simulate_cache, self.tpcc_hack) return self._train_global_models(resource_data_list, impact_data_list)
def estimate(self): """Train the mini-models :return: the map of the trained models """ resource_data_list, impact_data_list = global_data_constructing_util.get_data( self.input_path, self.mini_model_map, self.model_results_path, 0, False, self.ee_sample_interval, self.txn_sample_interval, self.network_sample_interval) return self._global_model_prediction(resource_data_list, impact_data_list)
def train(self): """Train the mini-models :return: the map of the trained models """ resource_data_list, impact_data_list = global_data_constructing_util.get_data( self.input_path, self.mini_model_map, self.model_results_path, self.warmup_period, self.use_query_predict_cache, self.add_noise, self.ee_sample_interval, self.txn_sample_interval, self.network_sample_interval) return self._train_global_models(resource_data_list, impact_data_list)
def predict_ou_data(self): """Generate grouped OU data with prediction """ data_lists = global_data_constructing_util.get_data( self.input_path, self.mini_model_map, self.model_results_path, self.warmup_period, self.use_query_predict_cache, self.add_noise, self.predict_ou_only, self.ee_sample_interval, self.txn_sample_interval, self.network_sample_interval) self.resource_data_list = data_lists[0] self.impact_data_list = data_lists[1]