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This first systematic and self-contained monograph on "Symbolic Data Analysis" presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data where the entries of a data table are, e. g., sets of categories or of numbers, intervals or probability distributions. Typical methods include: graphical displays using Zoom Stars, visualization and feature extraction by symbolic factor analysis, decision trees, discrimination, classification and clustering methods. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.
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Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data (Studies in Classification, Data Analysis, and Knowledge Organization)
February 3, 2000, Springer
Paperback
in English
- 1 edition
3540666192 9783540666196
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Book Details
First Sentence
"In many domains of human activities it is now quite common to record huge sets of data in large data bases."
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September 28, 2024 | Edited by MARC Bot | import existing book |
February 11, 2019 | Created by MARC Bot | import existing book |