Paper Info
Title
Visual Analytics for High Dimensional Data: Very Late Added Paper.
Abstract
A dataset with M items has 2M subsets anyone of which may be the one satisfying our objective. With a good data display and interactivity our fantastic pattern-recognition defeats the combinatorial explosion by extracting insights from the visual patterns. This is the core reason for data visualization. With parallel coordinates, as illustrated here, the search for relations in multivariate data is transformed into a 2-D pattern recognition problem. A geometric classification algorithm yields the classification rule explicitly and visually. The minimal set of variables, features, are found and ordered by their predictive value. A model of a country's economy reveals sensitivities, impact of constraints, trade-offs and economic sectors unknowingly competing for the same resources. A glimpse into this beautiful and powerful multidimensional geometry is shown at the end.
Year
DOI
Venue
2017
10.1145/3041021.3068853
WWW (Companion Volume)
Field
DocType
Citations 
Interactivity,Data mining,Clustering high-dimensional data,World Wide Web,Data visualization,Classification rule,Computer science,Multivariate statistics,Visual analytics,Parallel coordinates,Combinatorial explosion
Conference
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Alfred Inselberg11230165.81
Leonidas Anthopoulos27614.31