分析:综合高维算法分析与领域不可知论,面可视化分析

Edward Clarkson, J. Choo, John Turgeson, R. Decuir, Haesun Park
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引用次数: 2

摘要

我们提出了Lytic,一个领域独立的、面向面的视觉分析(VA)系统,用于大型数据集的交互式探索。它结合了一个灵活的UI,可以适应任意字符分隔值(CSV)数据集和算法预处理,以计算无监督降维和高维字段的聚类数据。它提供了各种可视化选项,这些选项需要最少的用户配置工作,并且在可视化类型和底层数据集之间提供一致的用户体验。过滤、比较和可视化操作协同工作,允许用户在操作之间无缝跳转,并寻求预期和意外数据假设的答案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lytic: synthesizing high-dimensional algorithmic analysis with domain-agnostic, faceted visual analytics
We present Lytic, a domain-independent, faceted visual analytic (VA) system for interactive exploration of large datasets. It combines a flexible UI that adapts to arbitrary character-separated value (CSV) datasets with algorithmic preprocessing to compute unsupervised dimension reduction and cluster data from high-dimensional fields. It provides a variety of visualization options that require minimal user effort to configure and a consistent user experience between visualization types and underlying datasets. Filtering, comparison and visualization operations work in concert, allowing users to hop seamlessly between actions and pursue answers to expected and unexpected data hypotheses.
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