An Introduction to Clustering with R | Buch

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Cover: 9789811305528 | An Introduction to Clustering with R | Paolo Giordani (u. a.) | Buch

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Sprache: Englisch

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Beschreibung

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.

Über den Autor

Paolo Giordani, Department of Statistical Sciences, Sapienza University of Rome

Maria Brigida Ferraro, Department of Statistical Sciences, Sapienza University of Rome

Francesca Martella, Department of Statistical Sciences, Sapienza University of Rome

Zusammenfassung

Provides a practical guide to clustering through real-life examples and case studies

Presents standard hard clustering and up-to-date soft clustering techniques

Gives a gradual introduction to R with detailed explanation of the code

Inhaltsverzeichnis

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.

Details

Erscheinungsjahr:	2020
Fachbereich:	Wahrscheinlichkeitstheorie
Genre:	Mathematik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Seiten:	360
Reihe:	Behaviormetrics: Quantitative Approaches to Human Behavior
Inhalt:	xvii 340 S. 112 s/w Illustr. 59 farbige Illustr. 340 p. 171 illus. 59 illus. in color.
ISBN-13:	9789811305528
ISBN-10:	9811305528
Sprache:	Englisch
Ausstattung / Beilage:	HC runder Rücken kaschiert
Einband:	Gebunden
Autor:	Giordani, Paolo Martella, Francesca Ferraro, Maria Brigida
Auflage:	1st ed. 2020
Hersteller:	Springer Singapore Springer Nature Singapore Behaviormetrics: Quantitative Approaches to Human Behavior
Maße:	241 x 160 x 25 mm
Von/Mit:	Paolo Giordani (u. a.)
Erscheinungsdatum:	28.08.2020
Gewicht:	0,705 kg

preigu-id: 113475154