Recently, our ongoing work on Interactive visualization approach for dimensionality reduction was presented at the 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA),
The procceedings have being added to IEEEXplore,
Peña-ünigarro, D. F., Salazar-Castro, J. A., Peluffo-Ordóñez, D. H., Rosero-Montalvo, P. D., Oña-Rocha, O. R., Isaza, A. A., ... & Theron, R. (2016, November). Interactive visualization methodology of high-dimensional data with a color-based model for dimensionality reduction. In Signal Processing, Images and Artificial Vision (STSIVA), 2016 XXI Symposium on (pp. 1-7). IEEE.
Nowadays, a consequence of data overload is that world's technology capacity to collect, communicate, and store large volumes of data is increasing faster than human analysis skills. Such an issue has motivated the development of graphic ways to visually represent and analyze high-dimensional data. Particularly, in this work, we propose a graphical interface that allow the combination of dimensionality reduction (DR) methods using a chromatic model to make data visualization more intelligible for humans. This interface is designed for an easy and interactive use, so that input parameters are given by the user via the selection of RGB values inside a given surface. Proposed interface enables (even non-expert) users to intuitively either select a concrete DR method or carry out a mixture of methods. Experimental results proves the usability of our interface making the selection or configuration of a DR-based visualization an intuitive and interactive task for the user.