Advanced Studies In Classification And Data Science

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Advanced Studies in Classification and Data Science

Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi
Advanced Studies in Classification and Data Science Book PDF

Author : Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi
Publisher : Springer Nature
Page : 506 pages
File Size : 54,5 Mb
Release : 2020-09-25
Category : Mathematics
ISBN : 9789811533112

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Advanced Studies in Classification and Data Science by Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi Pdf

This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems.

Advanced Studies in Classification and Data Science

Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi
Advanced Studies in Classification and Data Science Book PDF

Author : Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi
Publisher : Springer
Page : 524 pages
File Size : 49,7 Mb
Release : 2020-09-26
Category : Mathematics
ISBN : 9811533105

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Advanced Studies in Classification and Data Science by Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi Pdf

This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems.

Advances in Data Science and Classification

Alfredo Rizzi,Maurizio Vichi,Hans-Hermann Bock
Advances in Data Science and Classification Book PDF

Author : Alfredo Rizzi,Maurizio Vichi,Hans-Hermann Bock
Publisher : Springer Science & Business Media
Page : 678 pages
File Size : 47,5 Mb
Release : 2013-03-08
Category : Mathematics
ISBN : 9783642722530

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Advances in Data Science and Classification by Alfredo Rizzi,Maurizio Vichi,Hans-Hermann Bock Pdf

International Federation of Classification Societies The International Federation of Classification Societies (lFCS) is an agency for the dissemination of technical and scientific information concerning classification and multivariate data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) by the following Scientific Societies and Groups: - British Classification Society - BCS - Classification Society of North America - CSNA - Gesellschaft fUr Klassification - GfKI - Japanese Classification Society - JCS - Classification Group ofItalian Statistical Society - CGSIS - Societe Francophone de Classification - SFC Now the IFCS includes also the following Societies: - Dutch-Belgian Classification Society - VOC - Polish Classification Section - SKAD - Portuguese Classification Association - CLAD - Group at Large - Korean Classification Society - KCS IFCS-98, the Sixth Conference of the International Federation of Classification Societies, was held in Rome, from July 21 to 24, 1998. Five preceding conferences were held in Aachen (Germany), Charlottesville (USA), Edinburgh (UK), Paris (France), Kobe (Japan).

Advanced Studies in Behaviormetrics and Data Science

Tadashi Imaizumi,Atsuho Nakayama,Satoru Yokoyama
Advanced Studies in Behaviormetrics and Data Science Book PDF

Author : Tadashi Imaizumi,Atsuho Nakayama,Satoru Yokoyama
Publisher : Springer Nature
Page : 472 pages
File Size : 42,7 Mb
Release : 2020-04-17
Category : Social Science
ISBN : 9789811527005

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Advanced Studies in Behaviormetrics and Data Science by Tadashi Imaizumi,Atsuho Nakayama,Satoru Yokoyama Pdf

This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.

Data Science

Francesco Palumbo,Angela Montanari,Maurizio Vichi
Data Science Book PDF

Author : Francesco Palumbo,Angela Montanari,Maurizio Vichi
Publisher : Springer
Page : 342 pages
File Size : 52,5 Mb
Release : 2017-07-04
Category : Mathematics
ISBN : 9783319557236

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Data Science by Francesco Palumbo,Angela Montanari,Maurizio Vichi Pdf

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.

Advances in Classification and Data Analysis

Simone Borra,Roberto Rocci,Maurizio Vichi,Martin Schader
Advances in Classification and Data Analysis Book PDF

Author : Simone Borra,Roberto Rocci,Maurizio Vichi,Martin Schader
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 48,7 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642594717

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Advances in Classification and Data Analysis by Simone Borra,Roberto Rocci,Maurizio Vichi,Martin Schader Pdf

This volume contains a selection of papers presented at the biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica, which was held in Rome, July 5-6, 1999. From the originally submitted papers, a careful review process led to the selection of 45 papers presented in four parts as follows: CLASSIFICATION AND MULTIDIMENSIONAL SCALING Cluster analysis Discriminant analysis Proximity structures analysis and Multidimensional Scaling Genetic algorithms and neural networks MUL TIV ARIA TE DATA ANALYSIS Factorial methods Textual data analysis Regression Models for Data Analysis Nonparametric methods SPATIAL AND TIME SERIES DATA ANALYSIS Time series analysis Spatial data analysis CASE STUDIES INTERNATIONAL FEDERATION OF CLASSIFICATION SOCIETIES The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America - CSNA; Gesellschaft fUr Klassifikation - GfKI; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - CGSIS; Societe Francophone de Classification -SFC. Now the IFCS includes also the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Society -SKAD; Associayao Portuguesa de Classificayao e Analise de Dados -CLAD; Korean Classification Society -KCS; Group-at-Large.

Modern Quantification Theory

Shizuhiko Nishisato,Eric J. Beh,Rosaria Lombardo,Jose G. Clavel
Modern Quantification Theory Book PDF

Author : Shizuhiko Nishisato,Eric J. Beh,Rosaria Lombardo,Jose G. Clavel
Publisher : Springer Nature
Page : 231 pages
File Size : 48,5 Mb
Release : 2021-07-22
Category : Social Science
ISBN : 9789811624704

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Modern Quantification Theory by Shizuhiko Nishisato,Eric J. Beh,Rosaria Lombardo,Jose G. Clavel Pdf

This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis. These multiple identities are a consequence of its large number of properties that allow one to analyze and visualize the strength of variable association in an optimal solution. The book contains modern quantification theory for analyzing the association between two and more categorical variables in a variety of applicative frameworks. Visualization has attracted much attention over the past decades and given rise to controversial opinions. One may consider variations of plotting systems used in the construction of the classic correspondence plot, the biplot, the Carroll-Green-Schaffer scaling, or a new approach in doubled multidimensional space as presented in the book. There are even arguments for no visualization at all. The purpose of this book therefore is to shed new light on time-honored graphical procedures with critical reviews, new ideas, and future directions as alternatives. This stimulating volume is written with fresh new ideas from the traditional framework and the contemporary points of view. It thus offers readers a deep understanding of the ever-evolving nature of quantification theory and its practice. Part I starts with illustrating contingency table analysis with traditional joint graphical displays (symmetric, non-symmetric) and the CGS scaling and then explores logically correct graphs in doubled Euclidean space for both row and column variables. Part II covers a variety of mathematical approaches to the biplot strategy in graphing a data structure, providing a useful source for this modern approach to graphical display. Part II is also concerned with a number of alternative approaches to the joint graphical display such as bimodal cluster analysis and other statistical problems relevant to quantification theory.

Methods for the Analysis of Asymmetric Proximity Data

Giuseppe Bove,Akinori Okada,Donatella Vicari
Methods for the Analysis of Asymmetric Proximity Data Book PDF

Author : Giuseppe Bove,Akinori Okada,Donatella Vicari
Publisher : Springer Nature
Page : 203 pages
File Size : 47,6 Mb
Release : 2021-08-14
Category : Mathematics
ISBN : 9789811631726

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Methods for the Analysis of Asymmetric Proximity Data by Giuseppe Bove,Akinori Okada,Donatella Vicari Pdf

This book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data. A major objective of this book is to present to applied researchers a set of methods and algorithms for graphical representation and clustering of asymmetric relationships. Data frequently concern measurements of asymmetric relationships between pairs of objects from a given set (e.g., subjects, variables, attributes,...), collected in one or more matrices. Examples abound in many different fields such as psychology, sociology, marketing research, and linguistics and more recently several applications have appeared in technological areas including cybernetics, air traffic control, robotics, and network analysis. The capabilities of the presented algorithms are illustrated by carefully chosen examples and supported by extensive data analyses. A review of the specialized statistical software available for the applications is also provided. This monograph is highly recommended to readers who need a complete and up-to-date reference on methods for asymmetric proximity data analysis.

Classification, Clustering, and Data Analysis

Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock
Classification Clustering and Data Analysis Book PDF

Author : Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock
Publisher : Springer Science & Business Media
Page : 468 pages
File Size : 49,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642561818

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Classification, Clustering, and Data Analysis by Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock Pdf

The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.

Data Science, Classification, and Related Methods

Chikio Hayashi,Keiji Yajima,Hans H. Bock,Noboru Ohsumi,Yutaka Tanaka,Yasumasa Baba
Data Science Classification and Related Methods Book PDF

Author : Chikio Hayashi,Keiji Yajima,Hans H. Bock,Noboru Ohsumi,Yutaka Tanaka,Yasumasa Baba
Publisher : Springer Science & Business Media
Page : 780 pages
File Size : 41,9 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9784431659501

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Data Science, Classification, and Related Methods by Chikio Hayashi,Keiji Yajima,Hans H. Bock,Noboru Ohsumi,Yutaka Tanaka,Yasumasa Baba Pdf

This volume contains selected papers covering a wide range of topics, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery. The result is a broad view of the state of the art, making this an essential work not only for data analysts, mathematicians, and statisticians, but also for researchers involved in data processing at all stages from data gathering to decision making.

Survey Data Harmonization in the Social Sciences

Irina Tomescu-Dubrow,Christof Wolf,Kazimierz M. Slomczynski,J. Craig Jenkins
Survey Data Harmonization in the Social Sciences Book PDF

Author : Irina Tomescu-Dubrow,Christof Wolf,Kazimierz M. Slomczynski,J. Craig Jenkins
Publisher : John Wiley & Sons
Page : 420 pages
File Size : 42,5 Mb
Release : 2023-11-22
Category : Mathematics
ISBN : 9781119712183

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Survey Data Harmonization in the Social Sciences by Irina Tomescu-Dubrow,Christof Wolf,Kazimierz M. Slomczynski,J. Craig Jenkins Pdf

Survey Data Harmonization in the Social Sciences An expansive and incisive overview of the practical uses of harmonization and its implications for data quality and costs In Survey Data Harmonization in the Social Sciences, a team of distinguished social science researchers delivers a comprehensive collection of ex-ante and ex-post harmonization methodologies in the context of specific longitudinal and cross-national survey projects. The book examines how ex-ante and ex-post harmonization work individually and in relation to one another, offering practical guidance on harmonization decisions in the preparation of new data infrastructure for comparative research. Contributions from experts in sociology, political science, demography, economics, health, and medicine are included, all of which give voice to discipline-specific and interdisciplinary views on methodological challenges inherent in harmonization. The authors offer perspectives from Europe and the United States, as well as Africa, the latter of which provides insights rarely featured in survey research methodology handbooks. Readers will also find: A thorough introduction to approaches and concepts for survey data harmonization, as well as the effects of data harmonization on the overall survey research process Comprehensive explorations of ex-ante harmonization of survey instruments and non-survey data Practical discussions of ex-post harmonization of national social surveys, census and time use data, including explorations of survey data recycling A detailed overview of statistical issues linked to the use of harmonized survey data Perfect for upper undergraduate and graduate researchers who specialize in survey methodology, Survey Data Harmonization in the Social Sciences will also earn a place in the libraries of survey practitioners who engage in international research.

Supervised and Unsupervised Learning for Data Science

Michael W. Berry,Azlinah Mohamed,Bee Wah Yap
Supervised and Unsupervised Learning for Data Science Book PDF

Author : Michael W. Berry,Azlinah Mohamed,Bee Wah Yap
Publisher : Springer Nature
Page : 191 pages
File Size : 49,9 Mb
Release : 2019-09-04
Category : Technology & Engineering
ISBN : 9783030224752

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Supervised and Unsupervised Learning for Data Science by Michael W. Berry,Azlinah Mohamed,Bee Wah Yap Pdf

This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018). Includes new advances in clustering and classification using semi-supervised and unsupervised learning; Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning; Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.

Innovations in Multivariate Statistical Modeling

Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen
Innovations in Multivariate Statistical Modeling Book PDF

Author : Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen
Publisher : Springer Nature
Page : 434 pages
File Size : 44,8 Mb
Release : 2022-12-15
Category : Mathematics
ISBN : 9783031139710

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Innovations in Multivariate Statistical Modeling by Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen Pdf

Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.

Advances in Data Science

Edwin Diday,Rong Guan,Gilbert Saporta,Huiwen Wang
Advances in Data Science Book PDF

Author : Edwin Diday,Rong Guan,Gilbert Saporta,Huiwen Wang
Publisher : John Wiley & Sons
Page : 258 pages
File Size : 45,8 Mb
Release : 2020-02-05
Category : Business & Economics
ISBN : 9781786305763

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Advances in Data Science by Edwin Diday,Rong Guan,Gilbert Saporta,Huiwen Wang Pdf

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.

Advanced Classification Techniques for Healthcare Analysis

Chakraborty, Chinmay
Advanced Classification Techniques for Healthcare Analysis Book PDF

Author : Chakraborty, Chinmay
Publisher : IGI Global
Page : 424 pages
File Size : 55,5 Mb
Release : 2019-02-22
Category : Medical
ISBN : 9781522577973

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Advanced Classification Techniques for Healthcare Analysis by Chakraborty, Chinmay Pdf

Medical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals’ success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.