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]