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Field name	Details
Dewey Class	519.5
Title	An Introduction to Clustering with R ([EBook]) / by Paolo Giordani, Maria Brigida Ferraro, Francesca Martella.
Author	Giordani, Paolo
Added Personal Name	Ferraro, Maria Brigida
Added Personal Name	Martella, Francesca
Other name(s)	SpringerLink (Online service)
Edition statement	1st ed. 2020.
Publication	Singapore : : Springer Singapore : : Imprint: Springer, , 2020.
Physical Details	XVII, 340 p. 171 illus., 59 illus. in color. : online resource.
Series	Behaviormetrics: Quantitative Approaches to Human Behavior 2524-4027 ; ; 1
ISBN	9789811305535
Summary Note	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.:
Contents note	Section: Introduction -- 1.1 Introduction to clustering -- 1.2 R software -- 2. Section: Standard algorithms -- 2.1 Introduction -- 2.2 Distances and dissimilarities -- 2.3 Hierarchical methods -- 2.4 Non-hierarchical methods -- 2.5 Cluster validity -- 3. Section: Fuzzy algorithms -- 3.1 Introduction -- 3.2 Fuzzy K-means -- 3.3 Fuzzy K-medoids -- 3.4 Other fuzzy variants -- 3.5 Cluster validity -- 4. Section: Model-based algorithms -- 4.1 Introduction -- 4.2 Mixture of Gaussian distributions -- 4.3 Mixture of non-Gaussian distributions -- 4.4 Parsimonious mixture models.
Mode of acces to digital resource	Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format
System details note	- Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site	https://doi.org/10.1007/978-981-13-0553-5
Links to Related Works	Subject References: Applied Statistics . Biostatistics . Statistical Theory and Methods . Statistics . Statistics and Computing/Statistics Programs . Authors: author . Ferraro, Maria Brigida . Giordani, Paolo . Martella, Francesca . Corporate Authors: SpringerLink (Online service) . Series: Behaviormetrics: Quantitative Approaches to Human Behavior . Classification: 519.5 . 519.5 (DDC 23) .

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An Introduction to Clustering with R

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