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Ordinal And Symbolic Data Analysis

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Ordinal And Symbolic Data Analysis

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Author : Edwin Diday
language : en
Publisher: Springer
Release Date : 2011-10-08

Ordinal And Symbolic Data Analysis written by Edwin Diday and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-08 with Business & Economics categories.

Ordinal and symbolic data are increasingly finding applications in a number of domains, e.g. information technologies, economics, medicine. Here, one of the best teams working in the field presents the most recent advances in ordinal and symbolic data analysis. The new methods, developed here, are able to treat more complex or ordered data and express more knowledge than conventional data tables.

Ordinal And Symbolic Data Analysis

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Author : Edwin Diday
language : en
Publisher: Springer
Release Date : 1996-06-18

Analysis Of Symbolic Data

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Author : Hans-Hermann Bock
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Analysis Of Symbolic Data written by Hans-Hermann Bock and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.

This book 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. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.

Symbolic Data Analysis

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Author : Lynne Billard
language : en
Publisher: John Wiley & Sons
Release Date : 2012-05-14

Symbolic Data Analysis written by Lynne Billard and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-14 with Mathematics categories.

With the advent of computers, very large datasets have become routine. Standard statistical methods don’t have the power or flexibility to analyse these efficiently, and extract the required knowledge. An alternative approach is to summarize a large dataset in such a way that the resulting summary dataset is of a manageable size and yet retains as much of the knowledge in the original dataset as possible. One consequence of this is that the data may no longer be formatted as single values, but be represented by lists, intervals, distributions, etc. The summarized data have their own internal structure, which must be taken into account in any analysis. This text presents a unified account of symbolic data, how they arise, and how they are structured. The reader is introduced to symbolic analytic methods described in the consistent statistical framework required to carry out such a summary and subsequent analysis. Presents a detailed overview of the methods and applications of symbolic data analysis. Includes numerous real examples, taken from a variety of application areas, ranging from health and social sciences, to economics and computing. Features exercises at the end of each chapter, enabling the reader to develop their understanding of the theory. Provides a supplementary website featuring links to download the SODAS software developed exclusively for symbolic data analysis, data sets, and further material. Primarily aimed at statisticians and data analysts, Symbolic Data Analysis is also ideal for scientists working on problems involving large volumes of data from a range of disciplines, including computer science, health and the social sciences. There is also much of use to graduate students of statistical data analysis courses.

Symbolic Data Analysis And The Sodas Software

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Author : Edwin Diday
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-15

Symbolic Data Analysis And The Sodas Software written by Edwin Diday and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-15 with Mathematics categories.

Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical methods do not have the power or flexibility to make sense of very large datasets, and symbolic data analysis techniques have been developed in order to extract knowledge from such data. Symbolic data methods differ from that of data mining, for example, because rather than identifying points of interest in the data, symbolic data methods allow the user to build models of the data and make predictions about future events. This book is the result of the work f a pan-European project team led by Edwin Diday following 3 years work sponsored by EUROSTAT. It includes a full explanation of the new SODAS software developed as a result of this project. The software and methods described highlight the crossover between statistics and computer science, with a particular emphasis on data mining.

Advances In Data Science

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Author : Edwin Diday
language : en
Publisher: John Wiley & Sons
Release Date : 2020-02-05

Advances In Data Science written by Edwin Diday and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-05 with Business & Economics categories.

Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction. Special kinds of data (symbolic, network, complex, compositional) are increasingly frequent in data science. These data require specific methodologies, but there is a lack of reference work in this field. Advances in Data Science fills this gap. It presents a collection of up-to-date contributions by eminent scholars following two international workshops held in Beijing and Paris. The 10 chapters are organized into four parts: Symbolic Data, Complex Data, Network Data and Clustering. They include fundamental contributions, as well as applications to several domains, including business and the social sciences.

Analysis Of Ordinal Data

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Author : David K. Hildebrand
language : en
Publisher: SAGE
Release Date : 1977

Analysis Of Ordinal Data written by David K. Hildebrand and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Electronic books categories.

Ordinal data can be rank ordered but not assumed to have equal distances between categories. Using support by judges for civil rights measures and bussing as the primary example, this paper indicates how such data can best be analyzed.

Data Analysis Classification And Related Methods

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Author : Henk A.L. Kiers
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Data Analysis Classification And Related Methods written by Henk A.L. Kiers and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.

This volume contains a selection of papers presented at the Seven~h Confer ence of the International Federation of Classification Societies (IFCS-2000), which was held in Namur, Belgium, July 11-14,2000. From the originally sub mitted papers, a careful review process involving two reviewers per paper, led to the selection of 65 papers that were considered suitable for publication in this book. The present book contains original research contributions, innovative ap plications and overview papers in various fields within data analysis, classifi cation, and related methods. Given the fast publication process, the research results are still up-to-date and coincide with their actual presentation at the IFCS-2000 conference. The topics captured are: • Cluster analysis • Comparison of clusterings • Fuzzy clustering • Discriminant analysis • Mixture models • Analysis of relationships data • Symbolic data analysis • Regression trees • Data mining and neural networks • Pattern recognition • Multivariate data analysis • Robust data analysis • Data science and sampling The IFCS (International Federation of Classification Societies) The IFCS promotes the dissemination of technical and scientific information data analysis, classification, related methods, and their applica concerning tions.

Entropy Measures For Data Analysis

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Author : Karsten Keller
language : en
Publisher: MDPI
Release Date : 2019-12-19

Entropy Measures For Data Analysis written by Karsten Keller and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-19 with Science categories.

Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Data Analysis

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Author : Wolfgang A. Gaul
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Data Analysis written by Wolfgang A. Gaul and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.

"Data Analysis" in the broadest sense is the general term for a field of activities of ever-increasing importance in a time called the information age. It covers new areas with such trendy labels as, e.g., data mining or web mining as well as traditional directions emphazising, e.g., classification or knowledge organization. Leading researchers in data analysis have contributed to this volume and delivered papers on aspects ranging from scientific modeling to practical application. They have devoted their latest contributions to a book edited to honor a colleague and friend, Hans-Hermann Bock, who has been active in this field for nearly thirty years.

Ordinal And Symbolic Data Analysis

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