Overlay_dx - 自动化预测评估
Overlay\_dx - Automating forecasting evaluation
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中文总结 AI 辅助
本文提出overlay_dx，一种结合可视化与数值的新型时间序列预测评估指标，通过置信区间内预测百分比和覆盖曲线下面积，实现统一评估框架，改进模型比较。
中文摘要 AI 辅助
传统评估指标提供数值，但往往缺乏可理解性，阻碍了对模型性能的有效区分。我们的工作通过引入overlay_dx来应对这一挑战，这是一种衡量时间序列预测模型性能的新型评估指标。overlay_dx是一种可视化指标，表示预测值落在实际值周围置信区间内的百分比。此外，一旦绘制出评估结果，overlay_dx会计算覆盖曲线下的面积，提供一种在不同阈值和预测下预测值与实际值对齐程度的定量度量。通过大量实验，我们证明了我们的方法提供了一个统一的评估框架，结合了视觉和数值评估，从而改进模型比较，并为时间序列预测的进一步研究和优化工作提供有价值的见解。
英文摘要
Traditional evaluation metrics provides numerical values but often lack comprehensibility, hindering effective differentiation of model performances. Our work addresses this challenge by introducing overlay\_dx, a novel evaluation metric measuring the performance of time series prediction models. Overlay\_dx is a visual metric that represents the percentage of predictions falling within a confidence interval around actual values. Additionally, once evaluation results are plotted, overlay\_dx computes the area under the overlay curve, providing a quantitative measure of alignment between predicted and actual values across different thresholds and predictions. Through extensive experiments, we demonstrate that our approach offers a unified evaluation framework that combines both visual and numerical assessments, enabling improved model comparison and providing valuable insights for further research and optimization efforts in time series prediction.
发表机构
- Smile（Smile公司）
机构由 AI 辅助整理，请以论文原文为准。
