Approximated and user steerable tSNE for progressive visual analytics

Nicola Pezzotti, Boudewijn P.F. Lelieveldt, Laurens van der Maaten, Thomas Höllt, Elmar Eisemann, Anna Vilanova

Research output: Contribution to journalArticleAcademicpeer-review

66 Citations (Scopus)

Abstract

Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One key method for data analysis is dimensionality reduction, for example, to produce 2D embeddings that can be visualized and analyzed efficiently. t-Distributed Stochastic Neighbor Embedding (tSNE) is a well-suited technique for the visualization of high-dimensional data. tSNE can create meaningful intermediate results but suffers from a slow initialization that constrains its application in Progressive Visual Analytics. We introduce a controllable tSNE approximation (A-tSNE), which trades off speed and accuracy, to enable interactive data exploration. We offer real-time visualization techniques, including a density-based solution and a Magic Lens to inspect the degree of approximation. With this feedback, the user can decide on local refinements and steer the approximation level during the analysis. We demonstrate our technique with several datasets, in a real-world research scenario and for the real-time analysis of high-dimensional streams to illustrate its effectiveness for interactive data analysis.

Original languageEnglish
Article number7473883
Pages (from-to)1739-1752
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Volume23
Issue number7
DOIs
Publication statusPublished - 1 Jul 2017

Keywords

  • Approximate computation
  • Dimensionality reduction
  • High dimensional data
  • Progressive visual analytics

Fingerprint Dive into the research topics of 'Approximated and user steerable tSNE for progressive visual analytics'. Together they form a unique fingerprint.

  • Cite this

    Pezzotti, N., Lelieveldt, B. P. F., van der Maaten, L., Höllt, T., Eisemann, E., & Vilanova, A. (2017). Approximated and user steerable tSNE for progressive visual analytics. IEEE Transactions on Visualization and Computer Graphics, 23(7), 1739-1752. [7473883]. https://doi.org/10.1109/TVCG.2016.2570755