Instacart 2017

TASK: Given a user, a product, and the user's prior purchase history, predict whether or not the given product will be reordered in the user's next order

Tables:

orders (3.4m rows, 206k users):

order_id: order identifier

user_id: customer identifier

eval_set: which evaluation set this order belongs in (see SET described below)

order_number: the order sequence number for this user (1 = first, n = nth)

order_dow: the day of the week the order was placed on

order_hour_of_day: the hour of the day the order was placed on

days_since_prior: days since the last order, capped at 30

products (50k rows):/n

product_id: product identifier

product_name: name of the product

aisle_id: foreign key

department_id: foreign key

aisles (134 rows):

aisle_id: aisle identifier

aisle: the name of the aisle

deptartments (21 rows):

department_id: department identifier

department: the name of the department

order_products__SET (30m+ rows):

order_id: foreign key

product_id: foreign key

add_to_cart_order: order in which each product was added to cart

reordered: 1 if this product has been ordered by this user in the past, 0 otherwise

where SET is one of the four following evaluation sets (eval_set in orders): "prior": orders prior to that users most recent order (~3.2m orders) "train": training data supplied to participants (~131k orders) "test": test data reserved for machine learning competitions (~75k orders)