Build a late-delivery risk model

Suppose you have access to an anonymized order-creation dataset from a food delivery marketplace. The task is to estimate the probability that each delivery will be late, where a late order is defined as one whose actual drop-off timestamp occurs after the promised drop-off timestamp. Address the following design prompts: Target and split. Give a precise definition of the binary target and propose a chronological training/validation/test partition that prevents information…