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Wan_ 2b9dac4e37 | 1 year ago | |
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README.md | 1 year ago |
此数据集是一组描述客户订单随时间变化的关系文件。可以用来预测用户下一次订购的产品。该数据集是匿名的,包含来自20多万Instacart用户的300多万份杂货订单样本。对于每个用户,提供了4到100个订单,以及每个订单中购买的产品序列。数据集还提供下订单的星期和时间,以及订单之间的相对时间度量。
样本中每个实体(客户、产品、订单、通道等)都有一个关联的唯一id。大多数文件和变量名应该是自解释的。
aisles.csv构成如下:商品所属具体物品类别
aisle_id,aisle
1,prepared soups salads
2,specialty cheeses
3,energy granola bars
...
order_products___prior.csv文件:订单与商品信息
这些文件指定了每个订单中购买的产品。order_products__prior。csv包含所有客户以前的订单内容。”“重新排序”表示客户之前的订单包含该产品。请注意,某些订单将没有重新排序的项目。您可以预测没有重新排序项目的订单的显式“无”值。
该文件构成如下:
order_id,product_id,add_to_cart_order,reordered
1,49302,1,1
1,11109,2,1
1,10246,3,0
…
orders.csv文件:用户订单信息。该文件说明订单属于哪个集合(先前、训练、测试)。您仅预测测试集订单的重新排序项目。”order_dow’是一周中的一天。 该文件构成如下:
order_id,user_id,eval_set,order_number,order_dow,order_hour_of_day,days_since_prior_order 2539329,1,prior,1,2,08,
2398795,1,prior,2,3,07,15.0
473747,1,prior,3,3,12,21.0
…
products.csv构成如下:商品信息
product_id,product_name,aisle_id,department_id
1,Chocolate Sandwich Cookies,61,19
2,All-Seasons Salt,104,13
3,Robust Golden Unsweetened Oolong Tea,94,7
...
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