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Cluster Analysis And Applications


Cluster Analysis And Applications
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Cluster Analysis And Applications


Cluster Analysis And Applications
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Author : Rudolf Scitovski
language : en
Publisher: Springer Nature
Release Date : 2021-07-22

Cluster Analysis And Applications written by Rudolf Scitovski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-22 with Computers categories.


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.



Cluster Analysis For Applications


Cluster Analysis For Applications
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Author : Michael R. Anderberg
language : en
Publisher: Academic Press
Release Date : 2014-05-10

Cluster Analysis For Applications written by Michael R. Anderberg and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.


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


Cluster Analysis
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Author : Mark S. Aldenderfer
language : en
Publisher: Chronicle Books
Release Date : 1984-11

Cluster Analysis written by Mark S. Aldenderfer and has been published by Chronicle Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-11 with Mathematics categories.


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.



Classification Clustering And Data Analysis


Classification Clustering And Data Analysis
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Author : Krzystof Jajuga
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Classification Clustering And Data Analysis written by Krzystof Jajuga and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


The present volume contains a selection of papers presented at the Eighth Conference of the International Federation of Classification Societies (IFCS) which was held in Cracow, Poland, July 16-19, 2002. All originally submitted papers were subject to a reviewing process by two independent referees, a procedure which resulted in the selection of the 53 articles presented in this volume. These articles relate to theoretical investigations as well as to practical applications and cover a wide range of topics in the broad domain of classifi cation, data analysis and related methods. If we try to classify the wealth of problems, methods and approaches into some representative (partially over lapping) groups, we find in particular the following areas: • Clustering • Cluster validation • Discrimination • Multivariate data analysis • Statistical methods • Symbolic data analysis • Consensus trees and phylogeny • Regression trees • Neural networks and genetic algorithms • Applications in economics, medicine, biology, and psychology. Given the international orientation of IFCS conferences and the leading role of IFCS in the scientific world of classification, clustering and data anal ysis, this volume collects a representative selection of current research and modern applications in this field and serves as an up-to-date information source for statisticians, data analysts, data mining specialists and computer scientists.



Algorithms For Fuzzy Clustering


Algorithms For Fuzzy Clustering
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Author : Sadaaki Miyamoto
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-15

Algorithms For Fuzzy Clustering written by Sadaaki Miyamoto and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-15 with Computers categories.


Recently many researchers are working on cluster analysis as a main tool for exploratory data analysis and data mining. A notable feature is that specialists in di?erent ?elds of sciences are considering the tool of data clustering to be useful. A major reason is that clustering algorithms and software are ?exible in thesensethatdi?erentmathematicalframeworksareemployedinthealgorithms and a user can select a suitable method according to his application. Moreover clusteringalgorithmshavedi?erentoutputsrangingfromtheolddendrogramsof agglomerativeclustering to more recent self-organizingmaps. Thus, a researcher or user can choose an appropriate output suited to his purpose,which is another ?exibility of the methods of clustering. An old and still most popular method is the K-means which use K cluster centers. A group of data is gathered around a cluster center and thus forms a cluster. The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. A main reasonwhy we concentrate on fuzzy c-means is that most methodology and application studies infuzzy clusteringusefuzzy c-means,andfuzzy c-meansshouldbe consideredto beamajortechniqueofclusteringingeneral,regardlesswhetheroneisinterested in fuzzy methods or not. Moreover recent advances in clustering techniques are rapid and we requirea new textbook that includes recent algorithms.We should also note that several books have recently been published but the contents do not include some methods studied herein.



Data Clustering Theory Algorithms And Applications Second Edition


Data Clustering Theory Algorithms And Applications Second Edition
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Author : Guojun Gan
language : en
Publisher: SIAM
Release Date : 2020-11-10

Data Clustering Theory Algorithms And Applications Second Edition written by Guojun Gan and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-10 with Mathematics categories.


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 In Neuropsychological Research


Cluster Analysis In Neuropsychological Research
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Author : Daniel N. Allen
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-07-08

Cluster Analysis In Neuropsychological Research written by Daniel N. Allen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-08 with Psychology categories.


​​ ​Cluster analysis is a multivariate classification technique that allows for identification of homogenous subgroups within diverse samples based on shared characteristics. In recent years, cluster analysis has been increasingly applied to psychological and neuropsychological variables to address a number of empirical questions. This book provides an overview of cluster analysis, including statistical and methodological considerations in its application to neurobehavioral variables. First, an introduction to cluster analysis is presented that emphasizes issues of relevance to neuropsychological research, including controversies surrounding it use. Cluster analysis is then applied to clinical disorders that do not have an associated prototypical neuropsychological profile, including traumatic brain injury, schizophrenia, and health problems associated with homelessness. In a second application, cluster analysis is used to investigate the course of normal memory development. Finally, cluster analysis is applied to classification of brain injury severity in children and adolescents who sustained traumatic brain injury.



An Introduction To Clustering With R


An Introduction To Clustering With R
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Author : Paolo Giordani
language : en
Publisher: Springer
Release Date : 2020-11-15

An Introduction To Clustering With R written by Paolo Giordani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-15 with Mathematics categories.


The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.



Cluster Analysis For Data Mining And System Identification


Cluster Analysis For Data Mining And System Identification
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Author : János Abonyi
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-22

Cluster Analysis For Data Mining And System Identification written by János Abonyi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-22 with Mathematics categories.


The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.