Actas de congresos
Multidimensional projection with radial basis function and control points selection
Fecha
2014-03Registro en:
Pacific Visualization Symposium, 7, 2014, Yokohama, Japan.
9781479928736
Autor
Amorim, Elisa Portes dos Santos
Brazil, Emilio Vital
Nonato, Luis Gustavo
Samavati, Faramarz
Sousa, Mario Costa
Institución
Resumen
Multidimensional projection techniques provide an appealing approach
for multivariate data analysis, for their ability to translate
high-dimensional data into a low-dimensional representation that
preserves neighborhood information. In recent years, pushed by
the ever increasing data complexity in many areas, numerous advances
in such techniques have been observed, primarily in terms
of computational efficiency and support for interactive applications.
Both these achievements were made possible due to the introduction
of the concept of control points, which are used in many different
multidimensional projection techniques. However, little attention
has been drawn towards the process of control points selection.
In this work we propose a novel multidimensional projection technique
based on radial basis functions (RBF). Our method uses RBF
to create a function that maps the data into a low-dimensional space
by interpolating the previously calculated position of control points.
We also present a built-in method for the control points selection
based on “forward-selection” and “Orthogonal Least Squares” techniques.
We demonstrate that the proposed selection process allows
our technique to work with only a few control points while retaining
the projection quality and avoiding redundant control points