modify predict argument

diaryTraining.py

@@ -10,7 +10,7 @@ def train():
     # log保存路径，如果不加这个参数，日志默认保存在/temp路径下，不符合规范
     param = {'task': 'binary', 'lr': lr, 'lambda': l2_lambda, 'metric': 'auc',"log":"/data2/models/result"}
 
-    ffm_model.fit(param, DIRECTORY_PATH + "model_lr{}_lambda{}.out".format(lr, l2_lambda))
+    ffm_model.fit(param, DIRECTORY_PATH + "model.out")
 
     print("predicting")
     ffm_model.setTest(DIRECTORY_PATH + "test_ffm_data.csv")

predictDiary.py

@@ -52,7 +52,7 @@ def predict(user_profile):
     ffm_model.setSigmoid()
     #日志保存路径，如果不加这个参数，日志默认保存在/temp路径下，不符合规范
     param = {"log": "/data2/models/result"}
-    ffm_model.predict(param,DIRECTORY_PATH + "model_lr{}_lambda{}.out".format(lr, l2_lambda),
+    ffm_model.predict(param,DIRECTORY_PATH + "model.out",
                       DIRECTORY_PATH + "result/{0}_output.txt".format(user_profile['device_id']))
     print("预测结束")
     predict_save_to_local(user_profile, instance)

utils.py

@@ -16,7 +16,7 @@ def get_date():
     month = now.month
     day = now.day
     date = datetime(year,month,day)
-    data_start_date = (date - timedelta(days=38)).strftime("%Y-%m-%d")
+    data_start_date = (date - timedelta(days=6)).strftime("%Y-%m-%d")
     data_end_date = (date - timedelta(days=2)).strftime("%Y-%m-%d")
     validation_date = (date - timedelta(days=3)).strftime("%Y-%m-%d")
     test_date = data_end_date