Robust Cluster Analysis And Variable Selection
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Robust Cluster Analysis And Variable Selection
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Author : Gunter Ritter
language : en
Publisher: CRC Press
Release Date : 2014-09-02
Robust Cluster Analysis And Variable Selection written by Gunter Ritter and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-02 with Computers categories.
Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and real-time applications. The book provides clear guidance for the varying needs of both applications, describing scenarios in which accuracy and speed are the primary goals. Robust Cluster Analysis and Variable Selection includes all of the important theoretical details, and covers the key probabilistic models, robustness issues, optimization algorithms, validation techniques, and variable selection methods. The book illustrates the different methods with simulated data and applies them to real-world data sets that can be easily downloaded from the web. This provides you with guidance in how to use clustering methods as well as applicable procedures and algorithms without having to understand their probabilistic fundamentals.
Model Based Clustering And Classification For Data Science
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Author : Charles Bouveyron
language : en
Publisher: Cambridge University Press
Release Date : 2019-07-25
Model Based Clustering And Classification For Data Science written by Charles Bouveyron and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-25 with Mathematics categories.
Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Handbook Of Cluster Analysis
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Author : Christian Hennig
language : en
Publisher: CRC Press
Release Date : 2015-12-16
Handbook Of Cluster Analysis written by Christian Hennig and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-16 with Business & Economics categories.
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.The
Classification And Data Science In The Digital Age
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Author : Paula Brito
language : en
Publisher: Springer Nature
Release Date : 2023-12-07
Classification And Data Science In The Digital Age written by Paula Brito and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Computers categories.
The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and modeling to clustering and dimension reduction, from functional data analysis to time series analysis, and network analysis. The applications reflect new analyses in a variety of fields, including medicine, marketing, genetics, engineering, and education. The book comprises selected and peer-reviewed papers presented at the 17th Conference of the International Federation of Classification Societies (IFCS 2022), held in Porto, Portugal, July 19–23, 2022. The IFCS federates the classification societies and the IFCS biennial conference brings together researchers and stakeholders in the areas of Data Science, Classification, and Machine Learning. It provides a forum for presenting high-quality theoretical and applied works, and promoting and fostering interdisciplinary research and international cooperation. The intended audience is researchers and practitioners who seek the latest developments and applications in the field of data science and classification.
Soft Methods For Data Science
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Author : Maria Brigida Ferraro
language : en
Publisher: Springer
Release Date : 2016-08-30
Soft Methods For Data Science written by Maria Brigida Ferraro and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-30 with Technology & Engineering categories.
This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.
Cladag 2017 Book Of Short Papers
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Author : Francesca Greselin
language : en
Publisher: Universitas Studiorum
Release Date : 2017-09-29
Cladag 2017 Book Of Short Papers written by Francesca Greselin and has been published by Universitas Studiorum this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-29 with Mathematics categories.
This book is the collection of the Abstract / Short Papers submitted by the authors of the International Conference of The CLAssification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), held in Milan (Italy) on September 13-15, 2017.
Ki 2020 Advances In Artificial Intelligence
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Author : Ute Schmid
language : en
Publisher: Springer Nature
Release Date : 2020-09-08
Ki 2020 Advances In Artificial Intelligence written by Ute Schmid and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-08 with Computers categories.
This book constitutes the refereed proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020, held in Bamberg, Germany, in September 2020. The 16 full and 12 short papers presented together with 6 extended abstracts in this volume were carefully reviewed and selected from 62 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research. KI 2020 had a special focus on human-centered AI with highlights on AI and education and explainable machine learning. Due to the Corona pandemic KI 2020 was held as a virtual event.
Mixture Model Based Classification
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Author : Paul D. McNicholas
language : en
Publisher: CRC Press
Release Date : 2016-10-04
Mixture Model Based Classification written by Paul D. McNicholas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-04 with Mathematics categories.
"This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some time. The discussion of mixtures with heavy tails and asymmetric distributions will place this text as the authoritative, modern reference in the mixture modeling literature." (Douglas Steinley, University of Missouri) Mixture Model-Based Classification is the first monograph devoted to mixture model-based approaches to clustering and classification. This is both a book for established researchers and newcomers to the field. A history of mixture models as a tool for classification is provided and Gaussian mixtures are considered extensively, including mixtures of factor analyzers and other approaches for high-dimensional data. Non-Gaussian mixtures are considered, from mixtures with components that parameterize skewness and/or concentration, right up to mixtures of multiple scaled distributions. Several other important topics are considered, including mixture approaches for clustering and classification of longitudinal data as well as discussion about how to define a cluster Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. His research focuses on the use of mixture model-based approaches for classification, with particular attention to clustering applications, and he has published extensively within the field. He is an associate editor for several journals and has served as a guest editor for a number of special issues on mixture models.
Asymptotic Analysis Of Mixed Effects Models
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Author : Jiming Jiang
language : en
Publisher: CRC Press
Release Date : 2017-09-19
Asymptotic Analysis Of Mixed Effects Models written by Jiming Jiang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-19 with Mathematics categories.
Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models. The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book for a graduate-level course on mixed effects models, or asymptotic analysis.
Recent Developments And The New Direction In Soft Computing Foundations And Applications
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Author : Shahnaz N. Shahbazova
language : en
Publisher: Springer Nature
Release Date : 2020-07-10
Recent Developments And The New Direction In Soft Computing Foundations And Applications written by Shahnaz N. Shahbazova and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-10 with Technology & Engineering categories.
This book gathers authoritative contributions in the field of Soft Computing. Based on selected papers presented at the 7th World Conference on Soft Computing, which was held on May 29–31, 2018, in Baku, Azerbaijan, it describes new theoretical advances, as well as cutting-edge methods and applications. New theories and algorithms in fuzzy logic, cognitive modeling, graph theory and metaheuristics are discussed, and applications in data mining, social networks, control and robotics, geoscience, biomedicine and industrial management are described. This book offers a timely, broad snapshot of recent developments, including thought-provoking trends and challenges that are yielding new research directions in the diverse areas of Soft Computing.