LEADER 04081nam 22006855 450 001 9910863135103321 005 20250609111603.0 010 $a9789811305535 010 $a9811305536 024 7 $a10.1007/978-981-13-0553-5 035 $a(CKB)4100000011401114 035 $a(MiAaPQ)EBC6320880 035 $a(DE-He213)978-981-13-0553-5 035 $a(PPN)250213184 035 $a(MiAaPQ)EBC6320711 035 $a(EXLCZ)994100000011401114 100 $a20200827d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 13$aAn Introduction to Clustering with R /$fby Paolo Giordani, Maria Brigida Ferraro, Francesca Martella 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (346 pages) 225 1 $aBehaviormetrics: Quantitative Approaches to Human Behavior,$x2524-4035 ;$v1 311 08$a9789811305528 311 08$a9811305528 320 $aIncludes bibliographical references. 327 $aSection: 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. 330 $aThe purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interestedin applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book. 410 0$aBehaviormetrics: Quantitative Approaches to Human Behavior,$x2524-4035 ;$v1 606 $aStatistics 606 $aMathematical statistics$xData processing 606 $aStatistics 606 $aBiometry 606 $aStatistical Theory and Methods 606 $aStatistics and Computing 606 $aApplied Statistics 606 $aBiostatistics 615 0$aStatistics. 615 0$aMathematical statistics$xData processing. 615 0$aStatistics. 615 0$aBiometry. 615 14$aStatistical Theory and Methods. 615 24$aStatistics and Computing. 615 24$aApplied Statistics. 615 24$aBiostatistics. 676 $a519.53 700 $aGiordani$b Paolo$c(Writer on statistics),$4aut$4http://id.loc.gov/vocabulary/relators/aut$00 702 $aFerraro$b Maria Brigida$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMartella$b Francesca$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910863135103321 996 $aAn Introduction to Clustering with R$94165771 997 $aUNINA