Data Mining Applications with R

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Academic Press, 26 nov 2013 - 514 pagine

Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool.

R code, Data and color figures for the book are provided at the RDataMining.com website.

  • Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries
  • Presents various case studies in real-world applications, which will help readers to apply the techniques in their work
  • Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves
 

Pagine selezionate

Sommario

Power Grid Data Analysis with R and Hadoop
1
Picturing Bayesian Classifiers A Visual Data Mining Approach to Parameters Optimization
35
Discovery of Emergent Issues and Controversies in Anthropology Using Text Mining Topic Modeling and Social Ne
63
Text Mining and Network Analysis of Digital Libraries in R
95
Recommender Systems in R
117
Response Modeling in Direct Marketing A Data MiningBased Approach for Target Selection
153
Caravan Insurance Customer Profile Modeling with R
181
Selecting Best Features for Predicting Bank Loan Default
229
A RealTime Property Value Index Based on Web Data
273
Predicting Seabed Hardness Using Random Forest in R
299
Supervised Classification of Images Applied to Plankton Samples Using R and Zooimage
331
Crime Analyses Using R
367
Football Mining with R
397
Analyzing Internet DNSSEC Traffic with R for Resolving Platform Optimization
435
Index
457
Copyright

A Choquet Integral Toolbox and Its Application in Customer Preference Analysis
247

Altre edizioni - Visualizza tutto

Data Mining Applications with R
Yanchang Zhao,Yonghua Cen
Anteprima non disponibile - 2013
Data Mining Applications with R
Yanchang Zhao,Yonghua Cen
Anteprima non disponibile - 2017

Parole e frasi comuni

¼¼ accuracy algorithms analysis application backscatter Breiman calculated chapter Choquet Integral classifier cluster computed confusion matrix corpus covariates crime criteria cross-validation customers data frame data mining dataset direct marketing distribution document-term matrix documents estimated evaluation example F-score Figure FQDN frequency function fuzzy measure graph Hadoop identify implementation important indicates input Interaction Index iterations key/value pairs load machine learning MapReduce match messages method MLogit NNET object optimal output package version parameters performance plankton plot policies predictive model predictors prock random forest ratings regression response model retweeted Rfmtool RHIPE ROC curve routing table sample seabed hardness Section servers Shapley value statistics step subset support vector machine SVM model target techniques test set text mining token topic training set Twitter users visualization zooimage zooplankton

Informazioni sull'autore (2013)

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.

Informazioni bibliografiche

TitoloData Mining Applications with R
AutoriYanchang Zhao, Yonghua Cen
EditoreAcademic Press, 2013
ISBN0124115209, 9780124115200
Lunghezza514 pagine
  
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