IT training r and data mining examples and case studies zhao 2012 12 25
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IT training r and data mining examples and case studies zhao 2012 12 25
I IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case IT training r and data mining examples and case studies zhao 2012 12 25 studies of real-world applications. The supposed audience of this book are postgraduate students, researchers, and data miners who are interested in using R to do their data mining research and projects. Wc assume that readers already have a basic idea of data mining and also have some basic experi IT training r and data mining examples and case studies zhao 2012 12 25ence with R. We hope that this book will encourage more and more people to use R to do data mining work in their research and applications.This chapteIT training r and data mining examples and case studies zhao 2012 12 25
r introduces basic concepts and techniques for data mining, including a data mining process and popular data mining techniques. It also presents R andI IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case IT training r and data mining examples and case studies zhao 2012 12 25ess to discover interesting knowledge from large amounts of data (Han and Kamber. 2000). It is an interdisciplinary held with contributions from many areas, such as statistics, machine learning, information retrieval, pattern recognition, and bioinformatics. Data mining is widely used in many domain IT training r and data mining examples and case studies zhao 2012 12 25s, such as retail, finance, telecommunication, and social media.The main techniques for data mining include classification and prediction, clustering.IT training r and data mining examples and case studies zhao 2012 12 25
outlier detection, association rules, sequence analysis, time scries analysis, and text mining, and also some new techniques such as social network aI IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case IT training r and data mining examples and case studies zhao 2012 12 25et al., 2001: Witten and Frank, 2(X)5). In real-world applications, a data mining process can be broken into six major phases; business understanding, data understanding, data preparation, modeling, evaluation, and deployment, as defined by the CRISP-DM (Cross Industry Standard Process for Data Mini IT training r and data mining examples and case studies zhao 2012 12 25ng).1 This book focuses on the modeling phase, with data exploration and model evaluation involved in some chapters. Readers who want more informationIT training r and data mining examples and case studies zhao 2012 12 25
on data mining arc referred to online resources in Chapter 15.1 http://vzvzvz.crisp-din.org/.R and Data Mining1.2RR2 (R Development Core Team. 2012) I IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case IT training r and data mining examples and case studies zhao 2012 12 25tended easily via packages. There arc around 4000 packages available in the CRAN package repository.3 as on August 1.2012. More details about R arc available in All Introduction to R4 5 (Venables et al.. 2012) and R language Definition-(R Development Core learn. 2010b) at the CR AN website. R is wid IT training r and data mining examples and case studies zhao 2012 12 25ely used in both academia and industry.To help users to find out which R packages to use. the CRAN Task Views6 are a good guidance. They provide colleIT training r and data mining examples and case studies zhao 2012 12 25
ctions of packages for different tasks. Some task views related to data mining are:•Machine Learning and Statistical Learning;•Cluster Analysis and FiI IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case IT training r and data mining examples and case studies zhao 2012 12 25Card for Data Mining (see p. 221). which provides a comprehensive indexing of R packages and functions for data mining, categorized by their functionalities. Its latest version is available at http://WWW.rdatamining.com/docs.Readers who want more information on R are referred to online resources in IT training r and data mining examples and case studies zhao 2012 12 25Chapter 15.1.3 DatasetsThe datasets used in this book arc briefly described in this section.1.3.1The Iris DatasetThe iris dataset has been used for clIT training r and data mining examples and case studies zhao 2012 12 25
assification in many research publications. Il consists of 50 samples from each of three classes of iris flowers (Frank and Asuncion. 2010). One classI IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case IT training r and data mining examples and case studies zhao 2012 12 25p:/ /WWW. r - pro j ect. org /.x http://cran.r-project.org/.4http://cran.r-project.org/doc/manuals/R-intro.pdf.5http://cran.r-project.org/doc/manuals/R-lang.pdf.6http://cran.r-project.org/web/views/.Introduction3•sepal length in cm.•sepal width in cm,•petal length in cm,•petal width in cm. and•class IT training r and data mining examples and case studies zhao 2012 12 25: Iris Setosa. Iris Versicolour. and Iris Virginica.> str ị i ris)’dala.frame':150 obs.of 5 variables:I IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three case I IntroductionThis book introduces into using R for data mining. Il presents many examples of various data mining functionalities in R and three caseGọi ngay
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