t-viSNE: t-SNE投影的交互式评估与解释
t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections
AI总结：
针对t-SNE投影难解释、可信度不足的问题，提出交互式可视化工具t-viSNE，通过多视图组件支持多维度分析，经场景验证和用户研究证实有效，可提升t-SNE结果的可理解性。
摘要：
t分布随机邻域嵌入（t-SNE）作为多维数据可视化方法已得到广泛应用，在众多领域均有成功实践。尽管t-SNE投影实用性强，但可能难以解释甚至具有误导性，这会损害结果的可信度。理解t-SNE本身的细节及其输出中特定模式背后的原因可能是一项艰巨的任务，尤其对于降维领域的非专家而言更是如此。\n在本研究中，我们提出了t-viSNE，这是一款用于t-SNE投影可视化探索的交互式工具，支持分析人员从多个方面检查投影的准确性与含义，例如超参数的影响、距离与邻域保持情况、特定邻域的密度与代价，以及维度与视觉模式之间的相关性。我们设计了一套连贯、易用且高度集成的多视图组件用于t-SNE投影可视化。我们通过基于真实数据集的假设使用场景验证了t-viSNE的适用性与可用性，并展示了一项评估该工具有效性的用户研究结果。通过揭示运行t-SNE后通常会丢失的信息，我们希望为分析人员使用t-SNE提供支持，使其结果更易于理解。
英文摘要：
t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualization of multidimensional data has proven to be a popular approach, with successful applications in a wide range of domains. Despite their usefulness, t-SNE projections can be hard to interpret or even misleading, which hurts the trustworthiness of the results. Understanding the details of t-SNE itself and the reasons behind specific patterns in its output may be a daunting task, especially for non-experts in dimensionality reduction. In this work, we present t-viSNE, an interactive tool for the visual exploration of t-SNE projections that enables analysts to inspect different aspects of their accuracy and meaning, such as the effects of hyper-parameters, distance and neighborhood preservation, densities and costs of specific neighborhoods, and the correlations between dimensions and visual patterns. We propose a coherent, accessible, and well-integrated collection of different views for the visualization of t-SNE projections. The applicability and usability of t-viSNE are demonstrated through hypothetical usage scenarios with real data sets. Finally, we present the results of a user study where the tool's effectiveness was evaluated. By bringing to light information that would normally be lost after running t-SNE, we hope to support analysts in using t-SNE and making its results better understandable.
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