The visual display of quantitative information
The visual display of quantitative information
Component and correspondence analysis: dimension reduction by functional approximation
Component and correspondence analysis: dimension reduction by functional approximation
Modern mathematical statistics
Modern mathematical statistics
Envisioning information
A comparison of similarity measures of fuzzy values
Fuzzy Sets and Systems
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Finding patterns in time series: a dynamic programming approach
Advances in knowledge discovery and data mining
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The problem of data characterization of quantitative and qualitative measurement scales is stated in the context of an exploratory multivariate statistical analysis. An example from a car driving study is considered where the quantitative data correspond to the car and head movements, while the qualitative data correspond to objects being viewed--road, bridge, sign-post, etc. For each of these two sets, the literature is analyzed first in terms of data characterizing methods and relationship obtaining methods. Then we propose to evaluate and compare nine quantitative data characteriing methods: five corresponding to classic statistical indicators, two to crisp space windowing with either two or three windows, and two on fuzzy windowing with either two or three windows. Logically the last method appears as the best (according to our evaluation procedure). Then we propose a bidimensional fuzzy windowing instead of a crisp one to characterize the gaze positions. Finally the multiple correspondence analysis is used to investigate the membership value averages obtained from the characterization stage.