Название: An Introduction to Clustering with R Автор: Paolo Giordani, Maria Brigida Ferraro
Издательство: Springer
Год: 2020
Страниц: 346
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
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.
The book is primarily designed for practitioners who aim at analyzing data by using R for clustering purposes. Also, it can be used as a textbook for a (application-oriented) course on clustering. The prerequisites for reading this book do not go beyond some basic knowledge of matrices, statistics, and probability. Also, the reader should have some familiarity with computer programming in R.
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