用XGBoost预测亚马逊电子产品销量，改用销量区间提升准确率
Unlocking Your Sales Insights: Advanced XGBoost Forecasting Models for Amazon Products
- 将销量预测转为销量区间预测，提升模型表现
- 相比传统模型，XGBoost在亚马逊电子产品销量预测上更精准
- 适合电商运营、供应链规划人员参考
利润的重要影响因素之一是交易量。准确预测未来的交易量，对企业的运营和决策至关重要。电子商务为制造商提供了便捷的销售渠道，使销售额大幅提升。本研究提出一种基于XGBoost模型的解决方案，用于预测亚马逊平台消费电子产品的销售情况。初期仅预测具体销量值，效果不理想；通过将销售量数据替换为销售范围值后，模型表现显著提升。结果表明，相较于传统模型，XGBoost在该任务上展现出更优的预测性能。
原文摘要 · Abstract (English)
One of the important factors of profitability is the volume of transactions. An accurate prediction of the future transaction volume becomes a pivotal factor in shaping corporate operations and decision-making processes. E-commerce has presented manufacturers with convenient sales channels to, with which the sales can increase dramatically. In this study, we introduce a solution that leverages the XGBoost model to tackle the challenge of predict-ing sales for consumer electronics products on the Amazon platform. Initial-ly, our attempts to solely predict sales volume yielded unsatisfactory results. However, by replacing the sales volume data with sales range values, we achieved satisfactory accuracy with our model. Furthermore, our results in-dicate that XGBoost exhibits superior predictive performance compared to traditional models.
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