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3.49 kB
| # ============================================================ | |
| # Task: sales_flow_forecasting | |
| # ============================================================ | |
| # Task objective: | |
| # - Use historical sales of Store Sales store-category nodes to predict future sales. | |
| # - This is a timestamp-level time series forecasting task across multiple store-family nodes. | |
| # | |
| # Core semantics: | |
| # - sample is a decision timestamp. | |
| # - inputs are the historical time series available before that timestamp, plus future covariates known at prediction time, such as onpromotion and is_holiday. | |
| # - prediction is each episode's sales sequence over the future horizon. | |
| # - Future sales (protocol time series ID: sales) must be excluded from inputs to prevent label leakage. | |
| # ============================================================ | |
| task: | |
| id: sales_flow_forecasting | |
| type: time_series_forecasting | |
| description: > | |
| Predict future Store Sales flow from historical sales sequences for all | |
| (store_nbr, family) episodes. Each sample corresponds to one decision | |
| timestamp and uses index-reference labels. | |
| inherit_general: true | |
| sample: | |
| primary_key: timestamp | |
| label_mode: index_reference | |
| inputs: | |
| time_series: | |
| - fields: sales | |
| source: sales_flow_store_sales | |
| window: | |
| length: 28 | |
| unit: day | |
| sampling: | |
| native_rate: 1day | |
| task_rate: 1day | |
| downsample_method: mean | |
| upsample_method: ffill | |
| - fields: onpromotion | |
| source: store_family_known_future_onpromotion | |
| window: | |
| length: 28 | |
| unit: day | |
| sampling: | |
| native_rate: 1day | |
| task_rate: 1day | |
| downsample_method: mean | |
| upsample_method: ffill | |
| - fields: is_holiday | |
| source: store_family_known_future_holiday | |
| window: | |
| length: 28 | |
| unit: day | |
| sampling: | |
| native_rate: 1day | |
| task_rate: 1day | |
| downsample_method: mean | |
| upsample_method: ffill | |
| tabular_static: | |
| source: store_sales_static_metadata | |
| fields: | |
| - store_nbr | |
| - family | |
| - family_id | |
| - city | |
| - state | |
| - type | |
| - cluster | |
| graph: | |
| source: store_family_relation_graph | |
| prediction: | |
| field: sales | |
| source: sales_flow_store_sales | |
| horizon: | |
| length: 7 | |
| unit: day | |
| starts_after: timestamp | |
| stride: 7 | |
| label_storage: | |
| ref_column: target_series_ref | |
| shape_column: target_tensor_shape | |
| leakage: | |
| observed_past_only_columns: | |
| - sales | |
| known_future_columns: | |
| - onpromotion | |
| - is_holiday | |
| data_refs: | |
| time_series: | |
| sales_flow_store_sales: | |
| file: Store_Sales_protocol/input_multimodal/time_series/sales/sales.h5 | |
| value_field: sales | |
| native_grid_minutes: 1440 | |
| store_family_known_future_onpromotion: | |
| file: Store_Sales_protocol/input_multimodal/time_series/onpromotion/onpromotion.h5 | |
| value_field: onpromotion | |
| native_grid_minutes: 1440 | |
| store_family_known_future_holiday: | |
| file: Store_Sales_protocol/input_multimodal/time_series/is_holiday/is_holiday.h5 | |
| value_field: is_holiday | |
| tabular_static: | |
| store_sales_static_metadata: | |
| file: Store_Sales_protocol/input_multimodal/meta_features.csv | |
| id_column: episode_id | |
| graph: | |
| store_family_relation_graph: | |
| file: Store_Sales_protocol/input_multimodal/node_level_task_graphs/store_family_relation_graph/edge_infos.csv | |