| 摘 要: 数据挖掘技术运用于餐饮行业具有一定的社会价值，通过预测餐饮行业客流量，根据客流量多少餐厅合 理为顾客准备用餐,有利于提升顾客用餐体验，提高餐饮质量的同时让餐饮行业更高效运作。本文通过研究线性回归算 法与随机森林算法理论，提出将线性回归算法与随机森林算法融合的思想，将其应用在餐厅顾客回访数量预测，并通过 实验证明该思路的合理性和可实施性。通过实验对比，算法融合思路比线性回归算法准确率提高了约3.004%，比随机 森林算法提高了约2.022%。比以往大部分研究取得更优的预测效果，为数据挖掘技术在餐饮行业的应用提供了新的思 路。 |
| 关键词: 数据挖掘；线性回归；随机森林；算法融合；餐饮行业 |
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中图分类号: TP312
文献标识码: A
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| Combing Linear Regression Algorithm with Random Forest Algorithm to Predict Numbers of Restaurant Customers |
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YANG Senbin
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( College of Automation, Guangdong University of Technology, Guangzhou 525000, China)
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| Abstract: The application of data mining technology in the catering industry has a certain social value.Based on the prediction of the customer flow in the catering industry,restaurants can prepare meals for customers accordingly,which improves not only the customer experience of dining,but also the quality of service as well as more efficient operation of the catering industry.By studying linear regression algorithm and random forest algorithm theory,this paper puts forward the idea of combining linear regression algorithm with random forest algorithm,and applies it to the prediction of the numbers of customers return visits in restaurants,and proves the rationality and feasibility of the idea through experiments.Compared with linear regression algorithm with random forest algorithm,the accuracy of the combined algorithm is increased by about 3.004% and 2.022% respectively.Better prediction results have been obtained than most of the previous research,which provides a new way of thinking for the application of data mining technology in the catering industry. |
| Keywords: data mining;linear regression;random forests;algorithm combination;catering industry |
