EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book Discriminant Analysis and Clustering

Download or read book Discriminant Analysis and Clustering written by Ram Gnanadesikan and published by National Academies Press. This book was released on 1988-01-01 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Discriminant Analysis and Clustering

Download or read book Discriminant Analysis and Clustering written by National Research Council and published by National Academies Press. This book was released on 1988-02-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Classification and Clustering

Download or read book Classification and Clustering written by J. Van Ryzin and published by Elsevier. This book was released on 2014-05-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation discusses the relationship between multidimensional scaling and clustering, distribution problems in clustering, and botryology of botryology. The graph theoretic techniques for cluster analysis algorithms, data dependent clustering techniques, and linguistic approach to pattern recognition are also elaborated. This text likewise covers the discriminant analysis when scale contamination is present in the initial sample and statistical basis of computerized diagnosis using the electrocardiogram. Other topics include the simple histogram method for nonparametric classification and optimal smoothing of density estimates. This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.

Book Discriminant Analysis and Clustering

Download or read book Discriminant Analysis and Clustering written by and published by . This book was released on 1988 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Discriminant Analysis and Clustering

Download or read book Discriminant Analysis and Clustering written by and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Applied Multivariate Statistical Analysis and Related Topics with R

Download or read book Applied Multivariate Statistical Analysis and Related Topics with R written by Lang WU and published by EDP Sciences. This book was released on 2021-04-27 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate analysis is a popular area in statistics and data science. This book provides a good balance between conceptual understanding, key theoretical presentation, and detailed implementation with software R for commonly used multivariate analysis models and methods in practice.

Book Model Based Clustering and Classification for Data Science

Download or read book Model Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Clustering and Classification

Download or read book Clustering and Classification written by Phipps Arabie and published by World Scientific. This book was released on 1996 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering, variable selection and weighting, additive trees and other network models, relevance of neural network models to clustering, the role of computational complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.

Book Discriminant Analysis and Clustering

Download or read book Discriminant Analysis and Clustering written by National Research Council (U.S.). Panel on Discriminant Analysis, Classification, and Clustering and published by . This book was released on 1988 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Classification  Clustering  and Data Analysis

Download or read book Classification Clustering and Data Analysis written by Krzystof Jajuga and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Cluster Analysis and its Applications in Marketing Research

Download or read book Cluster Analysis and its Applications in Marketing Research written by Jagdish N. Sheth and published by Marketing Classics Press. This book was released on 2011-06-30 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Between Data Science and Applied Data Analysis

Download or read book Between Data Science and Applied Data Analysis written by Martin Schader and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume presents new developments in data analysis and classification and gives an overview of the state of the art in these scientific fields and relevant applications. Areas that receive considerable attention in the book are clustering, discrimination, data analysis, and statistics, as well as applications in economics, biology, and medicine it provides recent technical and methodological developments and a large number of application papers demonstrating the usefulness of the newly developed techniques.

Book Data Analysis  Classification  and Related Methods

Download or read book Data Analysis Classification and Related Methods written by Henk A.L. Kiers and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Model Based Clustering  Discriminant Analysis  and Density Estimation

Download or read book Model Based Clustering Discriminant Analysis and Density Estimation written by and published by . This book was released on 2000 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However, there is little systematic guidance associated with these methods for solving important practical questions that arise in cluster analysis, such as 'How many clusters are there?" "Which clustering method should be used?" and "How should outliers be handled?". We outline a general methodology for model-based clustering that provides a principled statistical approach to these issues. We also show that this can be useful for other problems in multivariate analysis, such as discriminant analysis and multivariate density estimation. We give examples from medical diagnosis, minefield detection, cluster recovery from noisy data, and spatial density estimation. Finally, we mention limitations of the methodology, and discuss recent developments in model-based clustering for non-Gaussian data, high-dimensional datasets, large datasets, and Bayesian estimation.

Book Classification and Clustering in Business Cycle Analysis

Download or read book Classification and Clustering in Business Cycle Analysis written by Ullrich Heilemann and published by Duncker & Humblot. This book was released on 2007-01-18 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of cyclical macroeconomic phenomena is an important field of econometric research. In the recent past, research interests have de-emphasized quantitative forecasting exercises and have addressed the qualitative diagnosis of the relative stance of the economy regarding »upswing«, »recession«, or »boom« periods, i. e. the classification of the state of the economy into a limited number of discrete states. In this context the principal challenge is to reduce the multifaceted and sometimes abundant quantitative information about the business cycle to such qualitative statements in an efficient way. For more than six years this task was the focus of the project »Multivariate determination and analysis of business cycles« within the SFB 475 »Reduction of complexity in multivariate data structures«, funded by the German Research Foundation (DFG). The necessity for complexity reduction is, of course, not unique to business cycle analysis but is studied in many fields and in a number of ways. This broad interest in the reduction of problem dimensionality and in the appropriate combination of data and of theory caused the RWI Essen and the Statistical Department of the University of Dortmund in January 2002 to hold a workshop at the RWI Essen where the findings of this and similar projects were presented and discussed. The present publication collects revised versions of the papers presented at this workshop. Although the workshop took place some five years ago, these papers mark an importent juncture in the development of business cycle research.

Book Advances in Data Science and Classification

Download or read book Advances in Data Science and Classification written by Alfredo Rizzi and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).