R and Data Mining Examples and Case Studies

Name: R and Data Mining Examples and Case Studies
Price: 29.75 USD
Availability: InStock
ISBN: 9780123969637

ISBN-10: 0123969638

ISBN-13: 9780123969637

Edition: 2012

Authors: Yanchang Zhao

List price: $79.95

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Description:

This book introduces into using R for data mining. Data mining techniques are widely used in government agencies, banks, insurance, retail, telecom, medicine and research. Recently, there is an increasing tendency to do data mining with R, a free software environment for statistical computing and graphics . According to a poll by KDnuggets.com in early 2011, R is the 2nd popular tool for data mining work. By introducing into using R for data mining, this book will have a broad audience from both academia and industry. It targets researchers in the field of data mining, postgraduate students who are interested in data mining, as well as data miners and analysts from industry. For example,…

Book details

List price: $79.95
Copyright year: 2012
Publisher: Elsevier Science & Technology
Publication date: 1/31/2013
Binding: Hardcover
Pages: 256
Size: 5.94" wide x 9.00" long x 1.00" tall
Weight: 1.232
Language: English

A Senior Data Mining Analyst in Australia Government since 2009. Before joining public sector, he was an Australian Postdoctoral Fellow (Industry) in the Faculty of Engineering & Information Technology at University of Technology, Sydney, Australia. His research interests include clustering, association rules, time series, outlier detection and data mining applications and he has over forty papers published in journals and conference proceedings. He is a member of the IEEE and a member of the Institute of Analytics Professionals of Australia, and served as program committee member for more than thirty international conferences.



List of Figures


List of Abbreviations



Introduction



Data Mining



R



Datasets



The Iris Dataset



The Bodyfat Dataset



Data Import and Export



Save and Load R Data



Import from and Export to .CSV Files



Import Data from SAS



Import/Export via ODBC



Read from Databases



Output to and Input from EXCEL Files



Data Exploration



Have a Look at Data



Explore Individual Variables



Explore Multiple Variables



More Explorations



Save Charts into Files



Decision Trees and Random Forest



Decision Trees with Package party



Decision Trees with Package rpart



Random Forest



Regression



Linear Regression



Logistic Regression



Generalized Linear Regression



Non-Linear Regression



Clustering



The k-Means Clustering



The k-Medoids Clustering



Hierarchical Clustering



Density-Based Clustering



Outlier Detection



Univariate Outlier Detection



Outlier Detection with LOF



Outlier Detection by Clustering



Outlier Detection from Time Series



Discussions



Time Series Analysis and Mining



Time Series Data in R



Time Series Decomposition



Time Series Forecasting



Time Series Clustering



Dynamic Time Warping



Synthetic Control Chart Time Series Data



Hierarchical Clustering with Euclidean Distance



Hierarchical Clustering with DTW Distance



Time Series Classification



Classification with Original Data



Classification with Extracted Features



k-NN Classification



Discussions



Further Readings



Association Rules



Basics of Association Rules



The Titanic Dataset



Association Rule Mining



Removing Redundancy



Interpreting Rules



Visualizing Association Rules



Discussions and Further Readings



Text Mining



Retrieving Text from Twitter



Transforming Text



Stemming Words



Building a Term-Document Matrix



Frequent Terms and Associations



Word Cloud



Clustering Words



Clustering Tweets



Clustering Tweets with the k-Means Algorithm



Clustering Tweets with the k-Medoids Algorithm



Packages, Further Readings, and Discussions



Social Network Analysis



Network of Terms



Network of Tweets



Two-Mode Network



Discussions and Further Readings



Case Study I: Analysis and Forecasting of House Price Indices



Importing HPI Data



Exploration of HPI Data



Trend and Seasonal Components of HPI



HPI Forecasting



The Estimated Price of a Property



Discussion



Case Study II: Customer Response Prediction and Profit Optimization



Introduction



The Data of KDD Cup 1998



Data Exploration



Training Decision Trees



Model Evaluation



Selecting the Best Tree



Scoring



Discussions and Conclusions



Case Study III: Predictive Modeling of Big Data with Limited Memory



Introduction



Methodology



Data and Variables



Random Forest



Memory Issue



Train Models on Sample Data



Build Models with Selected Variables



Scoring



Print Rules



Print Rules in Text



Print Rules for Scoring with SAS



Conclusions and Discussion



Online Resources



R Reference Cards



R



Data Mining



Data Mining with R



Classification/Prediction with R



Time Series Analysis with R



Association Rule Mining with R



Spatial Data Analysis with R



Text Mining with R



Social Network Analysis with R



Data Cleansing and Transformation with R



Big Data and Parallel Computing with R


R Reference Card for Data Mining


Bibliography


General Index


Package Index


Function Index