Advances In Data Science And Classification
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Data Science and Classification
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Author | : International Federation of Classification Societies. Conference |
Publsiher | : Springer |
Total Pages | : 0 |
Release | : 2006 |
Genre | : Cluster analysis |
ISBN | : 6610627371 |
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Provides methodological developments in data analysis and classification. Apart from structural and theoretical results, this book, of value to researchers, shows how to apply the developments to a variety of problems, for example, in medicine, microarray analysis, social network structures, and music.
Advanced Studies in Classification and Data Science
Author | : Tadashi Imaizumi,Akinori Okada,Sadaaki Miyamoto,Fumitake Sakaori,Yoshiro Yamamoto,Maurizio Vichi |
Publsiher | : Springer Nature |
Total Pages | : 506 |
Release | : 2020-09-25 |
Genre | : Mathematics |
ISBN | : 9789811533112 |
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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.
Machine Learning Paradigms
Author | : Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain |
Publsiher | : Springer |
Total Pages | : 223 |
Release | : 2019-03-16 |
Genre | : Technology & Engineering |
ISBN | : 9783030137434 |
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This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.
Data Science Classification and Related Methods
Author | : Chikio Hayashi,Keiji Yajima,Hans H. Bock,Noboru Ohsumi,Yutaka Tanaka,Yasumasa Baba |
Publsiher | : Springer Science & Business Media |
Total Pages | : 780 |
Release | : 2013-11-11 |
Genre | : Mathematics |
ISBN | : 9784431659501 |
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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.
Data Science
Author | : Francesco Palumbo,Angela Montanari,Maurizio Vichi |
Publsiher | : Springer |
Total Pages | : 342 |
Release | : 2017-07-04 |
Genre | : Mathematics |
ISBN | : 9783319557236 |
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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.
Model Based Clustering and Classification for Data Science
Author | : Charles Bouveyron,Gilles Celeux,T. Brendan Murphy,Adrian E. Raftery |
Publsiher | : Cambridge University Press |
Total Pages | : 446 |
Release | : 2019-07-25 |
Genre | : Business & Economics |
ISBN | : 9781108494205 |
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Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.
Advances in Data Science Methodologies and Applications
Author | : Gloria Phillips-Wren,Anna Esposito,Lakhmi C. Jain |
Publsiher | : Springer Nature |
Total Pages | : 333 |
Release | : 2020-08-26 |
Genre | : Technology & Engineering |
ISBN | : 9783030518707 |
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Big data and data science are transforming our world today in ways we could not have imagined at the beginning of the twenty-first century. The accompanying wave of innovation has sparked advances in healthcare, engineering, business, science, and human perception, among others. The tremendous advances in computing power and intelligent techniques have opened many opportunities for managing data and investigating data in virtually every field, and the scope of data science is expected to grow over the next decade. These future research achievements will solve old challenges and create new opportunities for growth and development. Thus, the research presented in this book is interdisciplinary and covers themes embracing emotions, artificial intelligence, robotics applications, sentiment analysis, smart city problems, assistive technologies, speech melody, and fall and abnormal behavior detection. The book is directed to the researchers, practitioners, professors and students interested in recent advances in methodologies and applications of data science. An introduction to the topic is provided, and research challenges and future research opportunities are highlighted throughout.
Classification Clustering and Data Analysis
Author | : Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock |
Publsiher | : Springer Science & Business Media |
Total Pages | : 468 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 9783642561818 |
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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.