Szczegóły publikacji
Opis bibliograficzny
Very fast interactive visualization of large sets of high-dimensional data / Witold DZWINEL, Rafał WCISŁO // Procedia Computer Science [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1877-0509. — 2015 — vol. 51, s. 572–581. — Bibliogr. s. 581, Abstr. — ICCS 2015 : International Conference On Computational Science : Computational Science at the Gates of Nature : June 1–3, 2015 in Reykjavík, Iceland
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 90113 |
|---|---|
| Data dodania do BaDAP | 2015-06-25 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.procs.2015.05.325 |
| Rok publikacji | 2015 |
| Typ publikacji | referat w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Procedia Computer Science |
Abstract
The embedding of high-dimensional data into 2D/3D space is the most popular way of data visualization. Despite recent advances in developing of very accurate dimensionality reduction algorithms, such as BH-SNE, Q-SNE and LoCH, their relatively high computational complexity still remains the obstacle for interactive visualization of truly large datasets consisting of M ∼ 106+ of high-dimensional N ∼ 103+ feature vectors. We show that a new clone of the multidimensional scaling (MDS) - nr-MDS - can be up to two orders of magnitude faster than the modern dimensionality reduction algorithms. We postulate its linear O(M) computational and memory complexities. Simultaneously, our method preserves in 2D/3D target spaces high separability of data, similar to that obtained by the state-of-the-art dimensionality reduction algorithms. We present the effects of nr-MDS application in visualization of data repositories such as 20 Newsgroups (M = 1.8.104), MNIST (M = 7.104) and REUTERS (M = 2.67.105). © The Authors