@@ -446,7 +446,7 @@ def predict_data_simple(df_input, city_pair, object_dir, predict_dir=".", pred_t
else:
drop_prob = round(length_drop / (length_rise + length_drop), 2)
# 依旧保持之前的降价判定,概率修改
- if drop_prob >= 0.6:
+ if drop_prob >= 0.7:
df_min_hours.loc[idx, 'simple_will_price_drop'] = 1
# df_min_hours.loc[idx, 'simple_drop_in_hours_dist'] = 'd1'
df_min_hours.loc[idx, 'flag_dist'] = 'd1'
@@ -78,7 +78,7 @@ def _process_one_task(row):
return None
drop_price_sample_size = int(task.get("drop_price_sample_size", "0"))
- if drop_price_sample_size < 3: # 丢弃历史降价样本数过少(小于3)的
+ if drop_price_sample_size < 2: # 丢弃历史降价样本数过少(小于2)的
from_date = task.get("from_date")