Evaluation of Sampling Methods for Scatterplots
論文傳送門 代碼 作者 清華大學 Jun Yuan Shouxing Xiang Shixia Liu 中南大學 Jiazhi Xia 西交利物浦大學 Lingyun Yu 摘要 給定一個有數萬甚至更多點的散點圖，一個自然的問題是，應該使用哪種採樣方法來創建一個小而「好」的散點圖，以實現更好的抽象。我們提出了一個用戶研究的結果，調查了不同的抽樣策略對多類散點圖的影響。本研究的主要目的是瞭解採樣方法
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相關文章
- 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
- 3. Variance Reduction Methods: a Quick Introduction to Importance Sampling
- 4. 論文筆記：Evaluation of local spatio-temporal features for action recognition
- 5. Evaluation of Deep Learning Toolkits
- 6. Non-Sampling Learning for Personalized Recommendation——筆記
- 7. Winglets: Visualizing Association with Uncertainty in Multi-class Scatterplots
- 8. 【Up-Sampling】《CARAFE：Content-Aware ReAssembly of FEatures》
- 9. 論文閱讀：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