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An Introduction to Clustering with R / by Paolo Giordani, Maria Brigida Ferraro, Francesca Martella

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Behaviormetrics: Quantitative Approaches to Human Behavior ; 1 | Springer eBook CollectionPublisher: Singapore : Springer Singapore, 2020Publisher: Singapore : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource(XVII, 340 p. 171 illus., 59 illus. in color.)ISBN:
  • 9789811305535
Subject(s): Additional physical formats: 9789811305528 | 9789811305542 | Erscheint auch als: 9789811305528 Druck-Ausgabe | Erscheint auch als: 9789811305542 Druck-AusgabeDDC classification:
  • 519.5 23
DOI: DOI: 10.1007/978-981-13-0553-5Online resources: Summary: 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.Summary: 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.PPN: PPN: 1728474841Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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