Interactive Dimensionality Reduction for Visual Analytics

Diaz, Ignacio;Cuadrado, Abel A.;Pérez, Daniel;Garcia, Francisco J.;Verleysen, Michel
(2014) 2014 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014) — Location: Bruges (Belgium) (23.April.2014)

Files

InteractiveDimensionalityReductionforVisualAnalytics.pdf
  • Restricted Access
  • Adobe PDF
  • 1.88 MB
Request a copy

Details

Authors
  • Diaz, IgnacioUniversity of Oviedo, Sapin
    Author
  • Cuadrado, Abel A.University of Oviedo, Sapin
    Author
  • Pérez, DanielUniversity of Oviedo, Sapin
    Author
  • Garcia, Francisco J.University of Oviedo, Sapin
    Author
  • Verleysen, MichelUCLouvain
    Author
Abstract
In this work, we present a novel approach for data visualization based on interactive dimensionality reduction (iDR). The main idea of the paper relies on considering for visualization the intermediate results of non-convex DR algorithms under changes on the metric of the input data space driven by the user. With an appropriate visualization interface, our approach allows the user to focus on the relationships among dynamically selected groups of variables, as well as to assess the impact of a single variable or groups of variables in the structure of the data.
Affiliations

Citations

  • APA
  • Chicago
  • FWB

Diaz, I., Cuadrado, A. A., Pérez, D., Garcia, F. J., & Verleysen, M. (2014). Interactive Dimensionality Reduction for Visual Analytics. Proceedings of ESANN 2014, 183-188. https://hdl.handle.net/2078.5/253934