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Published in:
2005 | OriginalPaper | Chapter
A New Framework for Multidimensional Data Analysis
Author : Shizuhiko Nishisato
Published in: Classification — the Ubiquitous Challenge
Publisher: Springer Berlin Heidelberg
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Our common sense tell us that continuous data contain more information than categorized data. To prove it, however, is not that straightforward because most continuous variables are typically subjected to linear analysis, and categorized data to nonlinear analysis. This discrepancy prompts us to put both data types on a comparable basis, which leads to a number of problems, in particular, how to define information and how to capture both linear and nonlinear relations between variables both continuous and categorical. This paper proposes a general framework for both types of data so that we may look at the original statement on information.