predict diary

src/models/esmm/diary_model.py

@@ -87,17 +87,13 @@ _float_columns = [
     "seven_vote_pure_rate",
     "fifteen_vote_pure_rate",
     "thirty_vote_pure_rate",
-    "sixty_vote_pure_rate",
-    "ninety_vote_pure_rate",
-    "history_vote_pure_rate",
-    "one_reply_pure_rate",
-    "three_reply_pure_rate",
-    "seven_reply_pure_rate",
-    "fifteen_reply_pure_rate",
-    "thirty_reply_pure_rate",
-    "sixty_reply_pure_rate",
-    "ninety_reply_pure_rate",
-    "history_reply_pure_rate",
+    # "sixty_vote_pure_rate",
+    # "ninety_vote_pure_rate",
+    # "history_vote_pure_rate",
+    # "one_reply_pure_rate",
+    # "three_reply_pure_rate",
+    # "seven_reply_pure_rate",
+    # "fifteen_reply_pure_rate",
 ]
 _categorical_columns = [
     "device_id", "past_consume_ability_history", "potential_consume_ability_history", "price_sensitive_history", "device_fd",
@@ -123,7 +119,6 @@ def model_predict_diary(device_id, diary_ids, device_dict, diary_dict, predict_f
             tmp.update(diary_info)
             features = {}
             for col in _int_columns:
-                print(col)
                 features[col] = _int64_feature(int(tmp[col]))
             for col in _float_columns:
                 features[col] = _float_feature(float(tmp[col]))

src/models/esmm/fe/diary_fe.py

@@ -185,10 +185,10 @@ FLOAT_COLUMNS = [
     "three_reply_pure_rate",
     "seven_reply_pure_rate",
     "fifteen_reply_pure_rate",
-    "thirty_reply_pure_rate",
-    "sixty_reply_pure_rate",
-    "ninety_reply_pure_rate",
-    "history_reply_pure_rate",
+    # "thirty_reply_pure_rate",
+    # "sixty_reply_pure_rate",
+    # "ninety_reply_pure_rate",
+    # "history_reply_pure_rate",
 ]
 CATEGORICAL_COLUMNS = [
     "device_id", "active_type", "past_consume_ability_history", "potential_consume_ability_history", "price_sensitive_history",