An Introduction to Clustering with R

An Introduction to Clustering with R
Author: Paolo Giordani
Publisher: Springer Nature
Total Pages: 340
Release: 2020-08-27
Genre: Mathematics
ISBN: 9811305536

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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.


An Introduction to Clustering with R
Language: en
Pages: 340
Authors: Paolo Giordani
Categories: Mathematics
Type: BOOK - Published: 2020-08-27 - Publisher: Springer Nature

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The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques fo
Practical Guide to Cluster Analysis in R
Language: en
Pages: 168
Authors: Alboukadel Kassambara
Categories: Education
Type: BOOK - Published: 2017-08-23 - Publisher: STHDA

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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 clu
Model-Based Clustering and Classification for Data Science
Language: en
Pages: 447
Authors: Charles Bouveyron
Categories: Mathematics
Type: BOOK - Published: 2019-07-25 - Publisher: Cambridge University Press

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Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Whi
Clustering
Language: en
Pages: 400
Authors: Rui Xu
Categories: Mathematics
Type: BOOK - Published: 2008-11-03 - Publisher: John Wiley & Sons

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This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity me
Finding Groups in Data
Language: en
Pages: 376
Authors: Leonard Kaufman
Categories: Mathematics
Type: BOOK - Published: 1990-03-22 - Publisher: Wiley-Interscience

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Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES).