Analysis of Symbolic Data
Subtitle: Exploratory Methods for Extracting Statistical Information from Complex Data (Studies in Classification, Data Analysis, and Knowledge Organization)
Contributors: Hans-Hermann Bock (Editor); Edwin Diday (Editor)
Edition: 1 edition
Publisher: Springer
Published: February 3, 2000
Language: eng
Format: Paperback
Number of pages: 425
ISBN-13: 9783540666196
Subjects: Business mathematics; Data capture & analysis; Databases & data structures; Probability & statistics; Multivariate analysis; Mathematical Statistics; Mathematics; Business / Economics / Finance; Statistics; Science/Mathematics; Probability & Statistics - General; Computer Science; Probability & Statistics - Multivariate Analysis; Business & Economics / Statistics; Computers-Computer Science; Mathematics-Probability & Statistics - Multivariate Analysis; Data mining
First sentence: In many domains of human activities it is now quite common to record huge sets of data in large data bases.
Description: 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.