Interactive Quantification of Categorical Variables in Mixed Data Sets
2008 (English)In: Information Visualisation, 2008. IV '08. 12th International Conference / [ed] Ebad Banissi, Liz Stuart, Mikael Jern, Gennady Andrienko, Francis T. Marchese, Nasrullah Memon, Reda Alhajj, Theodor G Wyeld, Remo Aslak Burkhard, Georges Grinstein, Dennis Groth, Anna Ursyn, Carsten Maple, Anthony Faiola and Brock Craft, Los Alamitos, California: IEEE Computer Society, 2008, 3-10 p.Conference paper (Refereed)
Data sets containing a combination of categorical and continuous variables (mixed data sets) are difficult to analyse since no generalized similarity measure exists for categorical variables. Quantification of categorical variables makes it possible to represent this type of data using techniques designed for numerical data. This paper presents a quantification process of categorical variables in mixed data sets that incorporates information on relationships among the continuous variables into the process, as well as utilizing the domain knowledge of a user. An interactive visualization environment using parallel coordinates as a visual interface is provided, where the user is able to control the quantification process and analyse the result. The efficiency of the approach is demonstrated using two mixed data sets.
Place, publisher, year, edition, pages
Los Alamitos, California: IEEE Computer Society, 2008. 3-10 p.
, IEEE International Conference on Information Visualisation, ISSN 1550-6037
Categorical data, mixed data, parallel coordinates, quantification, correspondence analysis, clustering
IdentifiersURN: urn:nbn:se:liu:diva-43480DOI: 10.1109/IV.2008.33ISI: 000259178400001Local ID: 73940ISBN: 978-0-7695-3268-4 (print)OAI: oai:DiVA.org:liu-43480DiVA: diva2:264339
12th International Conference Information Visualisation, IV '08, London, UK, 9-11 July 2008