Visual Exploration of High‐Dimensional Data through Subspace Analysis and Dynamic Projections

E-ISSN： 1467-8659|34|3|271-280

ISSN： 0167-7055

Source： COMPUTER GRAPHICS FORUM (ELECTRONIC), Vol.34, Iss.3, 2015-06, pp. : 271-280

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Visualnostics: Visual Guidance Pictograms for Analyzing Projections of High‐dimensional Data

COMPUTER GRAPHICS FORUM (ELECTRONIC), Vol. 34, Iss. 3, 2015-06 ,pp. : 291-300

John Wiley & Sons Inc

Access to resources Recommend Favorite

Subspace Clustering for High-Dimensional Data Using Cluster Structure Similarity

International Journal of Intelligent Information Technologies (IJIIT), Vol. 14, Iss. 3, 2018-07 ,pp. : 38-55

IGI Global_journal

Access to resources Recommend Favorite

Two-way analysis of high-dimensional collinear data

By Huopaniemi Ilkka Suvitaival Tommi Nikkilä Janne Orešič Matej Kaski Samuel

Data Mining and Knowledge Discovery, Vol. 19, Iss. 2, 2009-10 ,pp. : 261-276

Springer Publishing Company

Access to resources Recommend Favorite

Retrieval of high-dimensional visual data: current state, trends and challenges ahead

By Foncubierta-Rodríguez Antonio Müller Henning Depeursinge Adrien

Multimedia Tools and Applications, Vol. 69, Iss. 2, 2014-03 ,pp. : 539-567

Springer Publishing Company

Access to resources Recommend Favorite

Automatic Subspace Clustering of High Dimensional Data

By Agrawal Rakesh Gehrke Johannes Gunopulos Dimitrios Raghavan Prabhakar

Data Mining and Knowledge Discovery, Vol. 11, Iss. 1, 2005-07 ,pp. : 5-33

Springer Publishing Company

Access to resources Recommend Favorite