散点图中的视觉模型拟合估计：噪声量与离中心程度的影响
Visual Model Fit Estimation in Scatterplots: Influence of Amount and Decentering of Noise.
作者信息
Reimann Daniel, Blech Christine, Ram Nilam, Gaschler Robert
出版信息
IEEE Trans Vis Comput Graph. 2021 Sep;27(9):3834-3838. doi: 10.1109/TVCG.2021.3051853. Epub 2021 Jul 29.
PMID:33444142
Abstract
Scatterplots with a model enable visual estimation of model-data fit. In Experiment 1 (N = 62) we quantified the influence of noise-level on subjective misfit and found a negatively accelerated relationship. Experiment 2 showed that decentering of noise only mildly reduced fit ratings. The results have consequences for model-evaluation.
摘要
带有模型的散点图能够直观地评估模型与数据的拟合度。在实验1（N = 62）中，我们量化了噪声水平对主观不匹配的影响，发现了一种负加速关系。实验2表明，噪声的偏离只会轻微降低拟合评分。这些结果对模型评估具有重要意义。
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