Handbook of Cluster Analysis PDF Download
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Author: Christian Hennig
Publisher: CRC Press
ISBN: 1466551895
Category : Business & Economics
Languages : en
Pages : 753
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Book Description
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
Author: Christian Hennig
Publisher: CRC Press
ISBN: 1466551895
Category : Business & Economics
Languages : en
Pages : 753
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Book Description
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
Author: Alboukadel Kassambara
Publisher: STHDA
ISBN: 1542462703
Category : Cluster analysis
Languages : en
Pages : 187
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Book Description
Although there are several good books on unsupervised machine learning, we felt that many of them are too theoretical. This book provides practical guide to cluster analysis, elegant visualization and interpretation. It contains 5 parts. Part I provides a quick introduction to R and presents required R packages, as well as, data formats and dissimilarity measures for cluster analysis and visualization. Part II covers partitioning clustering methods, which subdivide the data sets into a set of k groups, where k is the number of groups pre-specified by the analyst. Partitioning clustering approaches include: K-means, K-Medoids (PAM) and CLARA algorithms. In Part III, we consider hierarchical clustering method, which is an alternative approach to partitioning clustering. The result of hierarchical clustering is a tree-based representation of the objects called dendrogram. In this part, we describe how to compute, visualize, interpret and compare dendrograms. Part IV describes clustering validation and evaluation strategies, which consists of measuring the goodness of clustering results. Among the chapters covered here, there are: Assessing clustering tendency, Determining the optimal number of clusters, Cluster validation statistics, Choosing the best clustering algorithms and Computing p-value for hierarchical clustering. Part V presents advanced clustering methods, including: Hierarchical k-means clustering, Fuzzy clustering, Model-based clustering and Density-based clustering.
Author: Brian S. Everitt
Publisher:
ISBN:
Category :
Languages : en
Pages : 122
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Book Description
Author: Paolo Giordani
Publisher: Springer Nature
ISBN: 9811305536
Category : Mathematics
Languages : en
Pages : 340
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Book Description
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.
Author: Oded Maimon
Publisher: Springer Science & Business Media
ISBN: 038725465X
Category : Computers
Languages : en
Pages : 1378
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Book Description
Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Author: Robert Nisbet
Publisher: Elsevier
ISBN: 0124166458
Category : Mathematics
Languages : en
Pages : 822
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Book Description
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Author: Mark S. Aldenderfer
Publisher: Chronicle Books
ISBN: 9780803923768
Category : Mathematics
Languages : en
Pages : 92
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Book Description
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.
Author: Rajiv Grover
Publisher: SAGE Publications
ISBN: 1452261539
Category : Business & Economics
Languages : en
Pages : 721
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Book Description
The Handbook of Marketing Research: Uses, Misuses, and Future Advances comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm. Divided into four parts, the Handbook addresses (1) the different nuances of delivering insights; (2) quantitative, qualitative, and online data gathering techniques; (3) basic and advanced data analysis methods; and (4) the substantial marketing issues that clients are interested in resolving through marketing research.
Author: Jacques A. Hagenaars
Publisher: Cambridge University Press
ISBN: 1139439235
Category : Social Science
Languages : en
Pages : 478
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Book Description
Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research.
Author: Brian S. Everitt
Publisher: CRC Press
ISBN: 1466580577
Category : Mathematics
Languages : en
Pages : 354
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Book Description
With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
