Title :
Fuzzy parallel coordinates
Author :
Hall, Lawrence O. ; Berthold, Michael R.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
The ability to visualize data often leads to new insights. Data that is more than three dimensional must be visualized as a series of projections or transformed into some other representation which usually causes a loss of detail. Parallel coordinates allow one to visualize data in two dimensions without a loss of information. In this paper, we discuss the use of parallel coordinates to visualize fuzzy data. Fuzzy data may consist of fuzzy rules, which can be viewed as cutting a swath through an n-dimensional space. Fuzzy clusters may also be considered as fuzzy data in a similar way. Examples are given from three domains. The examples show that parallel coordinates can be used to find extraneous fuzzy rules, separate fuzzy clusters as well as validate previous findings about data sets
Keywords :
data visualisation; fuzzy logic; data sets; data visualisation; extraneous fuzzy rules; fuzzy clusters; fuzzy data; fuzzy parallel coordinates; fuzzy rules; n-dimensional space; parallel coordinates; Computer science; Data analysis; Data engineering; Data mining; Data visualization; Fuzzy sets; Histograms; Multidimensional systems; Scattering; Springs;
Conference_Titel :
Fuzzy Information Processing Society, 2000. NAFIPS. 19th International Conference of the North American
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-6274-8
DOI :
10.1109/NAFIPS.2000.877389