def train_lr():
params = {
"offline_model_dir": "weights/lr",
}
params.update(params_common)
X_train, X_valid = load_data("train"), load_data("vali")
model = LogisticRegression("ranking", params, logger)
model.fit(X_train, validation_data=X_valid)
model.save_session()
def train_lr():
params = {
"offline_model_dir": "../weights",
}
params.update(params_common)
X_train, X_valid = load_data("train"), load_data("vali")
X_test = load_data("test")
# print(X_test['label'])
model = LogisticRegression("ranking", params, logger)
model.fit(X_train, validation_data=X_valid)
model.save_session()
model.predict(X_test, 'pred.txt')