fix train main function

predictDiary.py

@@ -100,9 +100,12 @@ if __name__ == "__main__":
         if empty:
             time.sleep(10)
         else:
+            old_device_id_list = pd.read_csv(DIRECTORY_PATH + "data_set_device_id.csv")["device_id"].values().tolist()
             for device_id in device_id_list:
-                router(device_id)
-
+                if device_id in old_device_id_list:
+                    router(device_id)
+                else:
+                    print("该用户不是老用户，不能预测")
             end = time.time()
             time_cost = (end - start)
             print("耗时{}秒".format(time_cost))

processData.py

@@ -66,7 +66,7 @@ def feature_en():
     device_id_df['device_id'] = data_set_device_id
     print("data_set_device_id :")
     print(device_id_df.head(2))
-    device_id_df.to_csv(DIRECTORY_PATH + "device_id.csv", index=False)
+    device_id_df.to_csv(DIRECTORY_PATH + "data_set_device_id.csv", index=False)
     return data, test_number, validation_number
 
 

train.py

@@ -5,10 +5,9 @@ from diaryCandidateSet import get_eachCityDiaryTop3000
 
 # 把数据获取、特征转换、模型训练的模型串联在一起
 if __name__ == "__main__":
-    data_fe = feature_en()
-    ffm_transform(data_fe)
+    data, test_number, validation_number = feature_en()
+    ffm_transform(data, test_number, validation_number)
     train()
-    print("end")
     # print('---------------prepare candidates--------------')
     # get_eachCityDiaryTop3000()