\n", + " | n_unique_products | \n", + "n_records | \n", + "cardinality_ratio | \n", + "n_records_per_product_mean | \n", + "n_records_per_product_var | \n", + "
---|---|---|---|---|---|
low | \n", + "2888 | \n", + "11635 | \n", + "0.248217 | \n", + "4.02874 | \n", + "11.995364 | \n", + "
moderate | \n", + "4841 | \n", + "12207 | \n", + "0.396576 | \n", + "2.521586 | \n", + "3.302065 | \n", + "
extreme | \n", + "6056 | \n", + "10749 | \n", + "0.563401 | \n", + "1.774934 | \n", + "1.142235 | \n", + "
low_test | \n", + "1890.0 | \n", + "3665.0 | \n", + "0.515689 | \n", + "1.939153 | \n", + "1.739546 | \n", + "
moderate_test | \n", + "3146.0 | \n", + "4959.0 | \n", + "0.634402 | \n", + "1.576287 | \n", + "0.777803 | \n", + "
extreme_test | \n", + "2613.0 | \n", + "3162.0 | \n", + "0.826376 | \n", + "1.210103 | \n", + "0.220388 | \n", + "
Pipeline(steps=[('binning',\n", + " BinNumberTransformer(feature_properties={'EVENT': 20,\n", + " 'NORMAL_PRICE': 1,\n", + " 'PG_ID_1': 4,\n", + " 'PG_ID_2': 4,\n", + " 'PG_ID_3': 4,\n", + " 'PROMOTION_TYPE': 2,\n", + " 'P_ID': 4,\n", + " 'SALES_PRICE': 1,\n", + " 'SCHOOL_HOLIDAY': 4,\n", + " 'dayofweek': 2,\n", + " 'dayofyear': 257,\n", + " 'price_ratio': 49})),\n", + " ('CB',\n", + " CBPoissonRegressor(feature_groups=['P_ID', 'PG_ID_1',\n", + " 'PG_ID_2', 'PG_ID_3',\n", + " 'dayofweek', 'dayofyear',\n", + " 'SA...\n", + " learn_rate=<function half_linear_learn_rate at 0x7fa6a51be680>,\n", + " maximal_iterations=50,\n", + " minimal_factor_change=0.001,\n", + " minimal_loss_change=0.001,\n", + " observers=[<cyclic_boosting.observers.PlottingObserver object at 0x7fa6a1cee740>,\n", + " <cyclic_boosting.observers.PlottingObserver object at 0x7fa6a1ceff40>],\n", + " smoother_choice=<cyclic_boosting.common_smoothers.SmootherChoiceGroupBy object at 0x7fa6a1cedc00>))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
Pipeline(steps=[('binning',\n", + " BinNumberTransformer(feature_properties={'EVENT': 20,\n", + " 'NORMAL_PRICE': 1,\n", + " 'PG_ID_1': 4,\n", + " 'PG_ID_2': 4,\n", + " 'PG_ID_3': 4,\n", + " 'PROMOTION_TYPE': 2,\n", + " 'P_ID': 4,\n", + " 'SALES_PRICE': 1,\n", + " 'SCHOOL_HOLIDAY': 4,\n", + " 'dayofweek': 2,\n", + " 'dayofyear': 257,\n", + " 'price_ratio': 49})),\n", + " ('CB',\n", + " CBPoissonRegressor(feature_groups=['P_ID', 'PG_ID_1',\n", + " 'PG_ID_2', 'PG_ID_3',\n", + " 'dayofweek', 'dayofyear',\n", + " 'SA...\n", + " learn_rate=<function half_linear_learn_rate at 0x7fa6a51be680>,\n", + " maximal_iterations=50,\n", + " minimal_factor_change=0.001,\n", + " minimal_loss_change=0.001,\n", + " observers=[<cyclic_boosting.observers.PlottingObserver object at 0x7fa6a1cee740>,\n", + " <cyclic_boosting.observers.PlottingObserver object at 0x7fa6a1ceff40>],\n", + " smoother_choice=<cyclic_boosting.common_smoothers.SmootherChoiceGroupBy object at 0x7fa6a1cedc00>))])
BinNumberTransformer(feature_properties={'EVENT': 20, 'NORMAL_PRICE': 1,\n", + " 'PG_ID_1': 4, 'PG_ID_2': 4,\n", + " 'PG_ID_3': 4, 'PROMOTION_TYPE': 2,\n", + " 'P_ID': 4, 'SALES_PRICE': 1,\n", + " 'SCHOOL_HOLIDAY': 4, 'dayofweek': 2,\n", + " 'dayofyear': 257, 'price_ratio': 49})
CBPoissonRegressor(feature_groups=['P_ID', 'PG_ID_1', 'PG_ID_2', 'PG_ID_3',\n", + " 'dayofweek', 'dayofyear', 'SALES_PRICE',\n", + " 'NORMAL_PRICE', 'price_ratio',\n", + " 'PROMOTION_TYPE', 'SCHOOL_HOLIDAY', 'EVENT',\n", + " ('P_ID', 'dayofyear'), ('P_ID', 'dayofweek'),\n", + " ('P_ID', 'SALES_PRICE'),\n", + " ('PG_ID_1', 'PROMOTION_TYPE'),\n", + " ('PG_ID_2', 'PROMOTION_TYPE'),\n", + " ('PG_ID_3', 'PROMOTION_TYPE'),\n", + " ('PG_ID_1', 'dayof...\n", + " learn_rate=<function half_linear_learn_rate at 0x7fa6a51be680>,\n", + " maximal_iterations=50, minimal_factor_change=0.001,\n", + " minimal_loss_change=0.001,\n", + " observers=[<cyclic_boosting.observers.PlottingObserver object at 0x7fa6a1cee740>,\n", + " <cyclic_boosting.observers.PlottingObserver object at 0x7fa6a1ceff40>],\n", + " smoother_choice=<cyclic_boosting.common_smoothers.SmootherChoiceGroupBy object at 0x7fa6a1cedc00>)
\n", + " | low | \n", + "moderate | \n", + "extreme | \n", + "
---|---|---|---|
CB | \n", + "0.514472 | \n", + "0.660931 | \n", + "0.567132 | \n", + "
LGBM | \n", + "0.517914 | \n", + "0.666845 | \n", + "0.580666 | \n", + "
defference | \n", + "0.003443 | \n", + "0.005914 | \n", + "0.013535 | \n", + "
\n", + " | low | \n", + "moderate | \n", + "extreme | \n", + "
---|---|---|---|
CB | \n", + "14.962774 | \n", + "16.414445 | \n", + "16.656764 | \n", + "
LGBM | \n", + "15.126136 | \n", + "16.729034 | \n", + "17.223597 | \n", + "
defference | \n", + "0.163362 | \n", + "0.314589 | \n", + "0.566832 | \n", + "