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Author:
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Languages : en
Pages :
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Author:
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Category :
Languages : en
Pages :
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Author: Oldemar RodrÃguez
Publisher:
ISBN:
Category :
Languages : en
Pages : 106
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Author: Paula Brito
Publisher:
ISBN: 9789899895553
Category :
Languages : en
Pages : 109
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Author: Javier Arroyo
Publisher:
ISBN: 9788469565759
Category :
Languages : en
Pages : 80
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Book Description
Author: Hans-Hermann Bock
Publisher: Springer Science & Business Media
ISBN: 3642571557
Category : Mathematics
Languages : en
Pages : 444
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Book Description
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.
Author: Edwin Diday
Publisher: John Wiley & Sons
ISBN: 9780470723555
Category : Mathematics
Languages : en
Pages : 476
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Book Description
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.
Author:
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Category :
Languages : en
Pages : 0
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Author: Christos H. Skiadas
Publisher: John Wiley & Sons
ISBN: 1119597579
Category : Mathematics
Languages : en
Pages : 286
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Book Description
This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models, and techniques, along with appropriate applications. Volume 1 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into three parts: Part 1 presents clustering and regression cases; Part 2 examines grouping and decomposition, GARCH and threshold models, structural equations, and SME modeling; and Part 3 presents symbolic data analysis, time series and multiple choice models, modeling in demography, and data mining.
Author: Paula Brito
Publisher: Springer Science & Business Media
ISBN: 3540735585
Category : Computers
Languages : en
Pages : 619
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Book Description
This volume presents recent methodological developments in data analysis and classification. It covers a wide range of topics, including methods for classification and clustering, dissimilarity analysis, consensus methods, conceptual analysis of data, and data mining and knowledge discovery in databases. The book also presents a wide variety of applications, in fields such as biology, micro-array analysis, cyber traffic, and bank fraud detection.
Author: Yiannis Dimotikalis
Publisher: John Wiley & Sons
ISBN: 1786306735
Category : Business & Economics
Languages : en
Pages : 306
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Book Description
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
