Analysis of Symbolic Data
Subtitle: Exploratory Methods for Extracting Statistical Information from Complex Data
By: edited by Hans-Hermann Bock, Edwin Diday
Contributors: Diday, Edwin
Series: Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814; Studies in classification, data analysis, and knowledge organization
Publisher: Springer Berlin Heidelberg; Imprint; Springer
Published: 2000
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 425
ISBN-13: 9783642571558
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.
Table of contents: title: Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective; title: The Classical Data Situation; title: Symbolic Data; title: Symbolic Objects; title: Generation of Symbolic Objects from Relational Databases; title: Descriptive Statistics for Symbolic Data; title: Visualizing and Editing Symbolic Objects; title: Similarity and Dissimilarity; title: Symbolic Factor Analysis; title: Discrimination: Assigning Symbolic Objects to Classes; title: Clustering Methods for Symbolic Objects; title: Symbolic Approaches for Three-way Data; title: Illustrative Benchmark Analyses; title: The SODAS Software Package.