#?data?file?path
online_train_file_path?=?‘./data/ccf_data_revised/ccf_online_stage1_train.csv‘
offline_train_file_path?=?‘./data/ccf_data_revised/ccf_offline_stage1_train.csv‘
offline_test_file_path?=?‘./data/ccf_data_revised/ccf_offline_stage1_test_revised.csv‘

#?split?data?path
active_user_offline_data_path?=?‘./data/data_split/active_user_offline_record.csv‘
active_user_online_data_path?=?‘./data/data_split/active_user_online_record.csv‘
offline_user_data_path?=?‘./data/data_split/offline_user_record.csv‘
online_user_data_path?=?‘./data/data_split/online_user_record.csv‘

train_path?=?‘./data/data_split/train_data/‘
train_feature_data_path?=?train_path?+?‘features/‘
train_raw_data_path?=?train_path?+?‘raw_data.csv‘
train_dataset_path?=?train_path?+?‘dataset.csv‘
train_raw_online_data_path?=?train_path?+?‘raw_online_data.csv‘

validate_path?=?‘./data/data_split/validate_data/‘
validate_feature_data_path?=?validate_path?+?‘features/‘
validate_raw_data_path?=?validate_path?+?‘raw_data.csv‘
validate_dataset_path?=?validate_path?+?‘dataset.csv‘
validate_raw_online_data_path?=?validate_path?+?‘raw_online_data.csv‘

predict_path?=?‘./data/data_split/predict_data/‘
predict_feature_data_path?=?predict_path?+?‘features/‘
predict_raw_data_path?=?predict_path?+?‘raw_data.csv‘
predict_dataset_path?=?predict_path?+?‘dataset.csv‘
predict_raw_online_data_path?=?predict_path?+?‘raw_online_data.csv‘

#?model?path
model_path?=?‘./data/model/model‘
model_file?=?‘/model‘
model_dump_file?=?‘/model_dump.txt‘
model_fmap_file?=?‘/model.fmap‘
model_feature_importance_file?=?‘/feature_importance.png‘
model_feature_importance_csv?=?‘/feature_importance.csv‘
model_train_log?=?‘/train.log‘
model_params?=?‘/param.json‘

val_diff_file?=?‘/val_diff.csv‘

#?submission?path
submission_path?=?‘./data/submission/submission‘
submission_hist_file?=?‘/hist.png‘
submission_file?=?‘/submission.csv‘

#?raw?field?name
user_label?=?‘User_id‘
merchant_label?=?‘Merchant_id‘
coupon_label?=?‘Coupon_id‘
action_label?=?‘Action‘
discount_label?=?‘Discount_rate‘
distance_label?=?‘Distance‘
date_received_label?=?‘Date_received‘
date_consumed_label?=?‘Date‘
probability_consumed_label?=?‘Probability‘

#?global?values
consume_time_limit?=?15

train_feature_start_time?=?‘20160201‘
train_feature_end_time?=?‘20160514‘
train_dataset_start_time?=?‘20160515‘
train_dataset_end_time?=?‘20160615‘

validate_feature_start_time?=?‘20160101‘
validate_feature_end_time?=?‘20160413‘
validate_dataset_start_time?=?‘20160414‘
validate_dataset_end_time?=?‘20160514‘

predict_feature_start_time?=?‘20160315‘
predict_feature_end_time?=?‘20160630‘
predict_dataset_start_time?=?‘20160701‘
predict_dataset_end_time?=?‘20160731‘

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\
?????文件????????2699??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\config.py
?????文件????????4075??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\data_split.py
?????文件???????13989??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\data_view.py
?????文件????????3216??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\dl.py
?????文件???????46597??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\feature_extract.py
?????文件????????2505??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\gen_data.py
?????文件????????3909??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\lightgbm.py
?????文件????????5035??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\predict.py
?????文件????????2929??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\problem.txt
?????文件?????????121??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\run_all.sh
?????文件????????1126??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\util.py
?????文件???????14507??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?1\xgb.py
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\
?????文件???????61847??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\all_data_training.sql
?????文件????????2587??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\data_split.sql
?????文件????????3987??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\data_view.sql
?????文件?????????438??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\draw_feature_importance.py
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\feature_extract\
?????文件????????4671??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\feature_extract\coupon_features.sql
?????文件????????8827??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\feature_extract\merchant_features.sql
?????文件???????13855??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\feature_extract\other_features.sql
?????文件???????28977??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\feature_extract\user_features.sql
?????文件????????4624??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\feature_extract\user_merchant_features.sql
?????文件????????8763??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\features.sql
?????文件???????10173??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\fillna.sql
?????目錄???????????0??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\gbdt\
?????文件????????2475??2018-03-08?06:06??O2O-Coupon-Usage-Forecast-master\code\charles\season?2\gbdt\gbdt1.sql
............此處省略101個文件信息