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Guided Stable Dynamic Projections
Computer Graphics Forum ( IF 2.5 ) Pub Date : 2021-06-29 , DOI: 10.1111/cgf.14291
E. F. Vernier 1, 2 , J. L. D. Comba 1 , A. C. Telea 3
Affiliation  

Projections aim to convey the relationships and similarity of high-dimensional data in a low-dimensional representation. Most such techniques are designed for static data. When used for time-dependent data, they usually fail to create a stable and suitable low dimensional representation. We propose two dynamic projection methods (PCD-tSNE and LD-tSNE) that use global guides to steer projection points. This avoids unstable movement that does not encode data dynamics while keeping t-SNE's neighborhood preservation ability. PCD-tSNE scores a good balance between stability, neighborhood preservation, and distance preservation, while LD-tSNE allows creating stable and customizable projections. We compare our methods to 11 other techniques using quality metrics and datasets provided by a recent benchmark for dynamic projections.

中文翻译:

引导稳定动态投影

投影旨在以低维表示形式传达高维数据的关系和相似性。大多数此类技术是为静态数据设计的。当用于时间相关数据时,它们通常无法创建稳定且合适的低维表示。我们提出了两种动态投影方法(PCD-tSNE 和 LD-tSNE),它们使用全局指南来引导投影点。这避免了不编码数据动态的不稳定运动,同时保持 t-SNE 的邻域保存能力。PCD-tSNE 在稳定性、邻域保留和距离保留之间取得了良好的平衡,而 LD-tSNE 允许创建稳定且可自定义的投影。我们使用最近动态投影基准提供的质量指标和数据集将我们的方法与其他 11 种技术进行比较。
更新日期:2021-06-29
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