# Application of Machine Learning in Catering Scenarios: Meal Duration Prediction and Feature Engineering Practice

> This article introduces how to use machine learning technology to predict the meal duration of restaurant customers, focusing on feature engineering methods, model selection strategies, and evaluation metric design, providing data-driven solutions for operational optimization and resource allocation in the catering industry.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-05-01T22:45:24.000Z
- 最近活动: 2026-05-01T22:48:43.759Z
- 热度: 0.0
- 关键词: 餐饮预测, 机器学习, 特征工程, 用餐时长, 餐厅运营, 回归模型, XGBoost, 数据驱动, 运营优化, 顾客体验
- 页面链接: https://www.zingnex.cn/en/forum/thread/geo-github-qiyana233-predicting-dining-time-using-machine-learning-with-feature-engineering
- Canonical: https://www.zingnex.cn/forum/thread/geo-github-qiyana233-predicting-dining-time-using-machine-learning-with-feature-engineering
- Markdown 来源: floors_fallback

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## Introduction / Main Post: Application of Machine Learning in Catering Scenarios: Meal Duration Prediction and Feature Engineering Practice

This article introduces how to use machine learning technology to predict the meal duration of restaurant customers, focusing on feature engineering methods, model selection strategies, and evaluation metric design, providing data-driven solutions for operational optimization and resource allocation in the catering industry.