Evaluation of Sampling Methods for Scatterplots
论文传送门 代码 作者 清华大学 Jun Yuan Shouxing Xiang Shixia Liu 中南大学 Jiazhi Xia 西交利物浦大学 Lingyun Yu 摘要 给定一个有数万甚至更多点的散点图，一个自然的问题是，应该使用哪种采样方法来创建一个小而“好”的散点图，以实现更好的抽象。我们提出了一个用户研究的结果，调查了不同的抽样策略对多类散点图的影响。本研究的主要目的是了解采样方法
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相关文章
- 1. Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Cl
- 2. Performance Evaluation Methods for Distributed MPP Databases - Best Practice for PostgreSQL
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- 4. 论文笔记：Evaluation of local spatio-temporal features for action recognition
- 5. Evaluation of Deep Learning Toolkits
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- 7. Winglets: Visualizing Association with Uncertainty in Multi-class Scatterplots
- 8. 【Up-Sampling】《CARAFE：Content-Aware ReAssembly of FEatures》
- 9. 论文阅读：RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems
- 10. [MICCAI 2019] Comparative Evaluation of Hand-Engineered and Deep-Learned Features for Neonatal Hip B