def train_on_local_cluster(self): self.set_conf() input_path = "../data/exampledata/LRLocalExampleData/a9a.train" LOCAL_FS = LocalFileSystem.DEFAULT_FS TMP_PATH = tempfile.gettempdir() save_path = LOCAL_FS + TMP_PATH + "/model" log_path = LOCAL_FS + TMP_PATH + "/log" # Set trainning data path self.conf.set(AngelConf.ANGEL_TRAIN_DATA_PATH, input_path) # Set save model path self.conf.set(AngelConf.ANGEL_SAVE_MODEL_PATH, save_path) # Set log path self.conf.set(AngelConf.ANGEL_LOG_PATH, log_path) # Set actionType train self.conf.set(AngelConf.ANGEL_ACTION_TYPE, MLConf.ANGEL_ML_TRAIN) runner = LRRunner() runner.train(self.conf)
def inc_train(self): self.set_conf() input_path = 'data/exampledata/LRLocalExampleData/a9a.train' LOCAL_FS = LocalFileSystem.DEFAULT_FS TMP_PATH = tempfile.gettempdir() load_path = LOCAL_FS + TMP_PATH + "/model" save_path = LOCAL_FS + TMP_PATH + "/newmodel" log_path = LOCAL_FS + TMP_PATH + "/log" # Set trainning data path self.conf[AngelConf.ANGEL_TRAIN_DATA_PATH] = input_path # Set load model path self.conf[AngelConf.ANGEL_LOAD_MODEL_PATH] = load_path # Set save model path self.conf[AngelConf.ANGEL_SAVE_MODEL_PATH] = save_path # Set log path self.conf[AngelConf.ANGEL_LOG_PATH] = log_path # Set actionType incremental train self.conf[AngelConf.ANGEL_ACTION_TYPE] = MLConf.ANGEL_ML_INC_TRAIN runner = LRRunner() runner.inc_train(self.conf)
def predict(self): self.set_conf() input_path = "../data/exampledata/LRLocalExampleData/a9a.test" LOCAL_FS = LocalFileSystem.DEFAULT_FS TMP_PATH = System.getProperty("java.io.tmpdir", "/tmp") load_path = LOCAL_FS + TMP_PATH + "/model" save_path = LOCAL_FS + TMP_PATH + "/model" log_path = LOCAL_FS + TMP_PATH + "/log" predict_path = LOCAL_FS + TMP_PATH + "/predict" # Set trainning data path self.conf.set(AngelConf.ANGEL_TRAIN_DATA_PATH, input_path) # Set load model path self.conf.set(AngelConf.ANGEL_LOAD_MODEL_PATH, load_path) # Set predict result path self.conf.set(AngelConf.ANGEL_PREDICT_PATH, predict_path) # Set log path self.conf.set(AngelConf.ANGEL_LOG_PATH, log_path) # Set actionType prediction self.conf.set(AngelConf.ANGEL_ACTION_TYPE, MLConf.ANGEL_ML_PREDICT()) runner = LRRunner() runner.predict(self.conf)