Estimated Delivery Model

Learn how to build Estimate Delivery model for the food delivery app.

3. Model

Features engineering

Features Feature engineering Description
Order features: subtotal, cuisine
Item features: price and type
Order type: group, catering
Merchant details
Store ID Store Embedding
Realtime feature Number of orders, number of dashers, traffic, travel estimates
Time feature Time of day (lunch/dinner), day of week, weekend, holiday
Historical Aggregates Past X weeks average delivery time for: Store/City/market/TimeOfDay
Similarity Average parking times, variance in historical times
Latitude/longitude Measure estimated driving time between delivery of order(to consumer) & restaurants

Training data

  • We can use historical deliveries for the last 6 months as training data. Historical deliveries include delivery data and actual total delivery time, store data, order data, customers data, location, and parking data.

Model

Gradient Boosted Decision Tree

  • Gradient Boosted Decision Tree sample

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