def fm_classification(self):
input_path = "./src/test/data/fm/a9a.train"
LOCAL_FS = LocalFileSystem.DEFAULT_FS
TMP_PATH = tempfile.gettempdir()
save_path = LOCAL_FS + TMP_PATH + "/model"
log_path = LOCAL_FS + TMP_PATH + "/LRlog"
# 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)
# Set learnType
self.conf.set(MLConf.ML_FM_LEARN_TYPE, "c")
# Set feature number
self.conf.set(MLConf.ML_FEATURE_NUM, str(124))
runner = FMRunner()
runner.train(self.conf)
angel_client = AngelClientFactory.get(self.conf)
angel_client.stop()
def fm_classification(self):
input_path = "./src/test/data/fm/a9a.train"
LOCAL_FS = LocalFileSystem.DEFAULT_FS
TMP_PATH = tempfile.gettempdir()
save_path = LOCAL_FS + TMP_PATH + "/model"
log_path = LOCAL_FS + TMP_PATH + "/LRlog"
# 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)
# Set learnType
self.conf.set(MLConf.ML_FM_LEARN_TYPE, "c")
# Set feature number
self.conf.set(MLConf.ML_FEATURE_NUM, str(124))
runner = FMRunner()
runner.train(self.conf)
angel_client = AngelClientFactory.get(self.conf)
angel_client.stop()
def train_on_local_cluster(self):
self.set_conf()
input_path = "./src/test/data/fm/food_fm_libsvm"
local_fs = LocalFileSystem.DEFAULT_FS
temp_path = tempfile.gettempdir()
save_path = local_fs + temp_path + "/model"
log_path = local_fs + temp_path + "/LRlog"
# Set training data path
self.conf[AngelConf.ANGEL_TRAIN_DATA_PATH] = input_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 train
self.conf[AngelConf.ANGEL_ACTION_TYPE] = MLConf.ANGEL_ML_TRAIN
runner = FMRunner()
runner.train(self.conf)
def train_on_local_cluster(self):
self.set_conf()
input_path = "data/fm/food_fm_libsvm"
LOCAL_FS = LocalFileSystem.DEFAULT_FS
TMP_PATH = tempfile.gettempdir()
save_path = LOCAL_FS + TMP_PATH + "/model"
log_path = LOCAL_FS + TMP_PATH + "/LRlog"
# Set trainning data path
self.conf[AngelConf.ANGEL_TRAIN_DATA_PATH] = input_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 train
self.conf[AngelConf.ANGEL_ACTION_TYPE] = MLConf.ANGEL_ML_TRAIN
runner = FMRunner()
runner.train(self.conf)
def train_on_local_cluster(self):
self.set_conf()
input_path = "./src/test/data/fm/food_fm_libsvm"
LOCAL_FS = LocalFileSystem.DEFAULT_FS
TMP_PATH = tempfile.gettempdir()
save_path = LOCAL_FS + TMP_PATH + "/model"
log_path = LOCAL_FS + TMP_PATH + "/LRlog"
# 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 = FMRunner()
runner.train(self.conf)
angel_client = AngelClientFactory.get(self.conf)
angel_client.stop()
def train_on_local_cluster(self):
self.set_conf()
input_path = "./src/test/data/fm/food_fm_libsvm"
LOCAL_FS = LocalFileSystem.DEFAULT_FS
TMP_PATH = tempfile.gettempdir()
save_path = LOCAL_FS + TMP_PATH + "/model"
log_path = LOCAL_FS + TMP_PATH + "/LRlog"
# 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 = FMRunner()
runner.train(self.conf)
angel_client = AngelClientFactory.get(self.conf)
angel_client.stop()