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A Study on a Predictive Model of Customer Defection in a Hotel Reservation Website

机译:饭店预订网站中顾客叛逃的预测模型研究

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This paper examines a hotel reservation website’s customer defection. Applying statistic and data mining technology including logistic regression and random forests, we examine customer database to identify the attributes that affect customer attrition and develop a model of customer defection in the hotel reservation website. The empirical evaluation results showed the model has 78.9% accuracy, which suggest that the proposed churn prediction technique exhibits satisfactory predictive effectiveness.
机译:本文研究了酒店预订网站的客户叛逃行为。应用包括Logistic回归和随机森林在内的统计和数据挖掘技术,我们检查客户数据库以识别影响客户流失的属性,并在酒店预订网站上开发客户叛逃模型。实证评估结果表明,该模型的准确率达到78.9%,表明所提出的客户流失预测技术具有令人满意的预测效果。

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