The train data is seperated by class [0 or 1] to make it easier for training GANs
campaign/csv_reservoir
| train
|- [data_class0 & data_class 1].csv/*.csv.gz
| validation
|- data.csv/*.csv.gz
| test
|- data.csv/*.csv.gz
cat_columns = ["exchange_id", "user_frequency", "site_id", "deal_id",
"channel_type", "size", "week_part",
"day_of_week", "dma_id", "isp_id", "fold_position",
"browser_language_id", "country_id", "conn_speed", "os_id",
"day_part",
"region_id", "browser_id", "hashed_app_id",
"interstitial", "device_id", "creative_id",
"browser", "browser_version", "os", "os_version",
"device_model",
"device_manufacturer", "device_type", "exchange_id_cs_vcr",
"exchange_id_cs_vrate",
"exchange_id_cs_ctr", "exchange_id_cs_category_id",
"exchange_id_cs_site_id",
"category_id", "cookieless", "cross_device"]
numeric_columns = ["id_vintage",
"exchange_viewability_rate", "exchange_ctr",
"exchange_vcr", *_bpr, *_bpf, *_pixel]
target = "conversion_target"
Ignore "column_weights"