00

alg-evaluat-system/model_evaluat/roc_ks.py

@@ -122,7 +122,7 @@ cvr_roc_data=pd.DataFrame(cursor.fetchall(),
 
 alg=['alg-4.0','alg-4.0.1',
      'alg-4.0.2','alg-4.0.4','alg-4.1','alg-4.2.1',
-     'alg-610','alg-act-tab','alg-online-learn223',
+     'alg-act-tab','alg-online-learn223',
      'alg-online-learn224','alg-online-weight',
      'alg-app-optimize', 'alg-act-count',
      'alg-fm-backend','BTM_AND_PC_31','Material_reform',

auto-spread/auto_manage/effect_eva.py

@@ -230,7 +230,7 @@ stat_slotad_cvr_merge.ix[stat_slotad_cvr_merge['cvr_bias1']<=1.5].shape[0]/stat_
 stat_slotad_cvr_merge.ix[(stat_slotad_cvr_merge['stat_cvr1_x']<=0.05) & (stat_slotad_cvr_merge['cvr_bias1']<=1.5)].shape[0]/stat_slotad_cvr_merge.ix[(stat_slotad_cvr_merge['stat_cvr1_x']<=0.05) & (stat_slotad_cvr_merge['cvr_bias1']>0)].shape[0]
 stat_slotad_cvr_merge.ix[(stat_slotad_cvr_merge['stat_cvr1_x']>0.05) & (stat_slotad_cvr_merge['cvr_bias1']<=1.5)].shape[0]/stat_slotad_cvr_merge.ix[(stat_slotad_cvr_merge['stat_cvr1_x']>0.05) & (stat_slotad_cvr_merge['cvr_bias1']>0)].shape[0]
 #低出价
-stat_slotad_cvr_merge['cvr_bias0']=stat_slotad_cvr_merge['stat_cvr2_x']/stat_slotad_cvr_merge['stat_cvr0_y']
+stat_slotad_cvr_merge['cvr_bias0']=stat_slotad_cvr_merge['stat_cvr0_x']/stat_slotad_cvr_merge['stat_cvr0_y']
 #综合0.86.5  高cvr时0.86  低cvr时0.85  按cvr=0.05分割   0.86.2
 stat_slotad_cvr_merge.ix[stat_slotad_cvr_merge['cvr_bias0']<=1.5].shape[0]/stat_slotad_cvr_merge.ix[stat_slotad_cvr_merge['cvr_bias0']>0].shape[0]
 stat_slotad_cvr_merge.ix[(stat_slotad_cvr_merge['stat_cvr0_x']<=0.05) & (stat_slotad_cvr_merge['cvr_bias0']<=1.5)].shape[0]/stat_slotad_cvr_merge.ix[(stat_slotad_cvr_merge['stat_cvr0_x']<=0.05) & (stat_slotad_cvr_merge['cvr_bias0']>0)].shape[0]

auto-spread/auto_manage/effect_eva2.0.py

@@ -106,7 +106,7 @@ ad_pre_cvr_eva['ad_pre_diff']=ad_pre_cvr_eva['cvr']/ad_pre_cvr_eva['ad_cvr']
 
 
 #综合80% 高cvr 81% 低cvr<0.02 35%  cvr<0.01 10%
-ad_pre_cvr_eva.ix[ad_pre_cvr_eva['ad_pre_diff']<1.5].shape[0]/ad_pre_cvr_eva.ix[ad_pre_cvr_eva['ad_pre_diff']>0].shape[0]#26%的准确率
+ad_pre_cvr_eva.ix[ad_pre_cvr_eva['ad_pre_diff']<1.5].shape[0]/ad_pre_cvr_eva.ix[ad_pre_cvr_eva['ad_pre_diff']>0].shape[0]
 ad_pre_cvr_eva.ix[(ad_pre_cvr_eva['ad_pre_diff']<1.5) & (ad_pre_cvr_eva['ad_cvr']>0.05)].shape[0]/ad_pre_cvr_eva.ix[(ad_pre_cvr_eva['ad_pre_diff']>0) & (ad_pre_cvr_eva['ad_cvr']>0.05)].shape[0]
 ad_pre_cvr_eva.ix[(ad_pre_cvr_eva['ad_pre_diff']<1.5) & (ad_pre_cvr_eva['ad_cvr']<=0.02)].shape[0]/ad_pre_cvr_eva.ix[(ad_pre_cvr_eva['ad_pre_diff']>0) & (ad_pre_cvr_eva['ad_cvr']<=0.02)].shape[0]
 

auto-spread/auto_manage/params.py

@@ -27,11 +27,12 @@ params_dict={
     }
 }
 
-params_key="NZ_K86_trusteeship_params"
-params_value=json.dumps(params_dict)
+params_key=params_value=json.dumps(params_dict)
 
 pool = redis.ConnectionPool(host='r-bp18da0abeaddc94285.redis.rds.aliyuncs.com',
                             password='hteK73Zxx3ji9LGCy2jBAZDJ6', port=6379, db=0)
 
 r = redis.Redis(connection_pool=pool)
-r.set(params_key,params_value)
\ No newline at end of file
+r.set(params_key,params_value)
+
+print(params_value)
\ No newline at end of file

auto-spread/auto_manage/samples_create.py

@@ -66,7 +66,8 @@ sql2='''CREATE TABLE if not exists advert.dws_not_luanch_create_samples_mxx as
     last_charge_status,
     last_activity_equal_status,
     city_id,
-    activity_use_type
+    activity_use_type,
+    day_last_match_tag_nums_equal_status,
     rank_num,ROW_NUMBER() OVER(PARTITION BY slotid ORDER BY rank_num) rnb
       from 
 	  (select *,cast(rand()*100000000 as double) rank_num  from advert.dws_advert_order_wide_v4_level_6_di