Cluster Analysis For Applications PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Cluster Analysis For Applications PDF full book. Access full book title Cluster Analysis For Applications.

Cluster Analysis for Applications

Cluster Analysis for Applications
Author: Michael R. Anderberg
Publisher: Academic Press
Total Pages: 376
Release: 2014-05-10
Genre: Mathematics
ISBN: 1483191397

Download Cluster Analysis for Applications Book in PDF, ePub and Kindle

Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis. Comprised of 10 chapters, this book begins with an introduction to the subject of cluster analysis and its uses as well as category sorting problems and the need for cluster analysis algorithms. The next three chapters give a detailed account of variables and association measures, with emphasis on strategies for dealing with problems containing variables of mixed types. Subsequent chapters focus on the central techniques of cluster analysis with particular reference to computational considerations; interpretation of clustering results; and techniques and strategies for making the most effective use of cluster analysis. The final chapter suggests an approach for the evaluation of alternative clustering methods. The presentation is capped with a complete set of implementing computer programs listed in the Appendices to make the use of cluster analysis as painless and free of mechanical error as is possible. This monograph is intended for students and workers who have encountered the notion of cluster analysis.


Cluster Analysis and Applications

Cluster Analysis and Applications
Author: Rudolf Scitovski
Publisher: Springer Nature
Total Pages: 277
Release: 2021-07-22
Genre: Computers
ISBN: 303074552X

Download Cluster Analysis and Applications Book in PDF, ePub and Kindle

With the development of Big Data platforms for managing massive amount of data and wide availability of tools for processing these data, the biggest limitation is the lack of trained experts who are qualified to process and interpret the results. This textbook is intended for graduate students and experts using methods of cluster analysis and applications in various fields. Suitable for an introductory course on cluster analysis or data mining, with an in-depth mathematical treatment that includes discussions on different measures, primitives (points, lines, etc.) and optimization-based clustering methods, Cluster Analysis and Applications also includes coverage of deep learning based clustering methods. With clear explanations of ideas and precise definitions of concepts, accompanied by numerous examples and exercises together with Mathematica programs and modules, Cluster Analysis and Applications may be used by students and researchers in various disciplines, working in data analysis or data science.


Data Clustering: Theory, Algorithms, and Applications, Second Edition

Data Clustering: Theory, Algorithms, and Applications, Second Edition
Author: Guojun Gan
Publisher: SIAM
Total Pages: 430
Release: 2020-11-10
Genre: Mathematics
ISBN: 1611976332

Download Data Clustering: Theory, Algorithms, and Applications, Second Edition Book in PDF, ePub and Kindle

Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.


Cluster Analysis

Cluster Analysis
Author: Mark S. Aldenderfer
Publisher: Chronicle Books
Total Pages: 92
Release: 1984-11
Genre: Mathematics
ISBN: 9780803923768

Download Cluster Analysis Book in PDF, ePub and Kindle

Although clustering--the classification of objects into meaningful sets--is an important procedure in the social sciences today, cluster analysis as a multivariate statistical procedure is poorly understood by many social scientists. This volume is an introduction to cluster analysis for social scientists and students.


Cluster Analysis

Cluster Analysis
Author: Brian S. Everitt
Publisher:
Total Pages: 122
Release: 1977
Genre:
ISBN:

Download Cluster Analysis Book in PDF, ePub and Kindle


Classification, Clustering, and Data Analysis

Classification, Clustering, and Data Analysis
Author: Krzystof Jajuga
Publisher: Springer Science & Business Media
Total Pages: 468
Release: 2012-12-06
Genre: Computers
ISBN: 3642561810

Download Classification, Clustering, and Data Analysis Book in PDF, ePub and Kindle

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.


Cluster Analysis and Data Mining

Cluster Analysis and Data Mining
Author: Ronald S. King
Publisher: Mercury Learning and Information
Total Pages: 300
Release: 2015-05-12
Genre: Computers
ISBN: 1942270135

Download Cluster Analysis and Data Mining Book in PDF, ePub and Kindle

Cluster analysis is used in data mining and is a common technique for statistical data analysis used in many fields of study, such as the medical & life sciences, behavioral & social sciences, engineering, and in computer science. Designed for training industry professionals or for a course on clustering and classification, it can also be used as a companion text for applied statistics. No previous experience in clustering or data mining is assumed. Informal algorithms for clustering data and interpreting results are emphasized. In order to evaluate the results of clustering and to explore data, graphical methods and data structures are used for representing data. Throughout the text, examples and references are provided, in order to enable the material to be comprehensible for a diverse audience. A companion disc includes numerous appendices with programs, data, charts, solutions, etc. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. FEATURES *Places emphasis on illustrating the underlying logic in making decisions during the cluster analysis *Discusses the related applications of statistic, e.g., Ward’s method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.) *Contains separate chapters on JAN and the clustering of categorical data *Includes a companion disc with solutions to exercises, programs, data sets, charts, etc.


Classification, Clustering, and Data Mining Applications

Classification, Clustering, and Data Mining Applications
Author: International Federation of Classification Societies. Conference
Publisher: Springer Science & Business Media
Total Pages: 676
Release: 2004-06-09
Genre: Computers
ISBN: 3540220143

Download Classification, Clustering, and Data Mining Applications Book in PDF, ePub and Kindle

Modern data analysis stands at the interface of statistics, computer science, and discrete mathematics. This volume describes new methods in this area, with special emphasis on classification and cluster analysis. Those methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.


Finding Groups in Data

Finding Groups in Data
Author: Leonard Kaufman
Publisher: Wiley-Interscience
Total Pages: 376
Release: 1990-03-22
Genre: Mathematics
ISBN:

Download Finding Groups in Data Book in PDF, ePub and Kindle

Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.