Data Doubling and Fuzzy Coding

Authored by: Michael Greenacre

Visualization and Verbalization of Data

Print publication date:  April  2014
Online publication date:  April  2014

Print ISBN: 9781466589803
eBook ISBN: 9781466589810
Adobe ISBN:

10.1201/b16741-18

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Abstract

An important aspect of Benzécri’s French school of data analysis is the recoding of data prior to visualization by correspondence analysis (CA), a theme treated in detail in the book by Murtagh (2005). The method of CA is seen as a universal tool for visualizing data of any kind, once recoded into a suitable form. To understand what makes a data set suitable for CA, one has to consider the elements of a frequency table, which is the primary object on which CA is applicable, and which needs no pretransformation:

Each cell of a frequency table is a count.

The row or column frequencies are expressed relative to their marginal totals as profile vectors.

The marginal frequencies of the table provide masses that weight the row and column profiles in the measure of variance and in the dimension reduction.

The chi-square distance between profiles inherently standardizes the profile elements.

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