Comparative evaluation of the Scatter Plot Matrix and Parallel Coordinates Plot Matrix

Hugh Garner, S. Fernstad
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引用次数: 0

Abstract

The Scatter Plot Matrix (SPLOM) and the Parallel Coordinates Plot Matrix (PCPM) are frequently used in exploratory data analysis for multivariate data to explore pairwise relationships, clustering and outliers. The SPLOM and PCPM are complex visualization methods with many potential interactions between data, task and visual representation. While numerous studies exist evaluating the SPLOM and Parallel Coordinates Plot (PCP) there is, to the best of our knowledge, no existing study evaluating the PCPM. This pilot study presents an evaluation of the performance of the SPLOM and PCPM for a set of common explorative tasks and identifies key directions for future work. The overall results indicate a minimal performance difference between the visualization methods for most tasks, but with significant variance between users, interactions between data features and response by method, and strong user preferences depending on task. As such, we recommend careful consideration of the background of potential users when choosing a method, and/or the use of complementary or linked views. Further work is required to understand the particular mechanisms impacting users' highly variable performance with the PCPM.
散点图矩阵与平行坐标图矩阵的比较评价
散点图矩阵(SPLOM)和平行坐标图矩阵(PCPM)在多变量数据的探索性数据分析中经常被使用,以探索成对关系、聚类和异常值。SPLOM和PCPM是复杂的可视化方法,在数据、任务和可视化表示之间存在许多潜在的相互作用。虽然已有许多研究对SPLOM和平行坐标图(PCP)进行了评价,但据我们所知,尚无对PCPM进行评价的研究。这项试点研究对SPLOM和PCPM的性能进行了评估,并为一系列共同的探索性任务确定了未来工作的关键方向。总体结果表明,对于大多数任务,可视化方法之间的性能差异很小,但在用户之间、数据特征之间的交互和方法响应之间、以及用户对任务的强烈偏好之间存在显著差异。因此,我们建议在选择方法时仔细考虑潜在用户的背景,和/或使用互补或链接视图。需要进一步的工作来理解影响PCPM高度可变的用户性能的特定机制。
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