update ad abnormal videos

ad_video_data_update.py

@@ -89,9 +89,11 @@ def predict_video_share_rate(video_initial_df, dt, data_key, data_param, top10_a
     redis_data[-1] = group_ad_share_rate_mean
     # 异常视频给定值：mean/3
     if top10_abnormal_video_ids is not None:
+        abnormal_video_param = config_.AD_ABNORMAL_VIDEOS_PARAM.get(data_key, 1)
+        print(data_key, data_param, abnormal_video_param)
         for abnormal_video_id in top10_abnormal_video_ids:
-            print(abnormal_video_id, group_ad_share_rate_mean, group_ad_share_rate_mean/3)
-            redis_data[int(abnormal_video_id)] = group_ad_share_rate_mean / 3
+            print(abnormal_video_id, group_ad_share_rate_mean, group_ad_share_rate_mean * abnormal_video_param)
+            redis_data[int(abnormal_video_id)] = group_ad_share_rate_mean * abnormal_video_param
     if len(redis_data) > 0:
         redis_helper = RedisHelper()
         redis_helper.add_data_with_zset(key_name=key_name, data=redis_data, expire_time=2 * 24 * 3600)

config.py

@@ -751,6 +751,19 @@ class BaseConfig(object):
         }
     }
 
+    # 广告模型异常视频数据处理参数
+    AD_ABNORMAL_VIDEOS_PARAM = {
+        'data1': 1/3,  # vlog
+        'data2': 1/2,  # 票圈视频
+        'data3': 1/3,  # 内容精选
+        'data4': 1/3,  # 票圈短视频
+        'data5': 1/3,  # 老好看视频
+        'data6': 1/3,  # 票圈最惊奇
+        'data1:7days': 1/3,  # vlog 优化4
+        'data4:7days': 1/3,  # 票圈短视频 优化4
+    }
+
+
     # 广告模型用户分组类别
     AD_MID_GROUP = {
         'class1': [