English(EN) Predictive Analytics in E-Commerce for CustomerBehavior Forecasting using hybrid Ret-DNN withXGBoost Model

混合AI模型提升电子商务客户行为预测能力

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-16 13:41

研究人员开发了一种混合Ret-DNN与XGBoost模型，以改进电子商务中的客户行为预测。该模型结合了用于特征提取的深度神经网络和用于预测的梯度提升，并使用了来自一家英国在线零售商的数据。所提出的模型实现了0.2193的平均绝对误差，优于现有的Ret-DNN模型。 AI

影响该混合模型为寻求理解和预测客户购买行为的电子商务平台提供了更高的准确性。

排序理由该集群包含一篇详细介绍特定应用新AI模型的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv cs.LG TIER_1 English(EN) · Degala Pushpa Sri, Mayank Atreya, Lakshmi. H, Navin Chhibber, Mukesh Soni · 2026-06-17 04:00

Predictive Analytics in E-Commerce for CustomerBehavior Forecasting using hybrid Ret-DNN withXGBoost Model

arXiv:2606.17931v1 Announce Type: new Abstract: In recent years, electronic (E) commerce services have rapidly increased in the daily lives of people, which helpsthem to purchase products online. However, retail platforms have struggled to understand customer behavior and make it…
arXiv cs.LG TIER_1 English(EN) · Mukesh Soni · 2026-06-16 13:41

Predictive Analytics in E-Commerce for CustomerBehavior Forecasting using hybrid Ret-DNN withXGBoost Model

In recent years, electronic (E) commerce services have rapidly increased in the daily lives of people, which helpsthem to purchase products online. However, retail platforms have struggled to understand customer behavior and make it difficult to predict their future purchases. To…