Data mining for business analytics: concepts, techniques, and applications in R

Galit Shmueli, Peter C Bruce, Inbal Yahav, Nitin R Patel, Kenneth C Lichtendahl

Research output: Book/ReportBook

Abstract

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.-- Provided by Publisher.
Original languageEnglish
Place of PublicationHoboken, New Jersey
Publisherwiley
Number of pages577
ISBN (Electronic)9781118879368, 9781118956632
StatePublished - 2018
Externally publishedYes

ULI Keywords

  • uli
  • Business mathematics -- Computer programs
  • Business -- Data processing
  • Data mining
  • R (Computer program language)
  • Electronic data processing -- Business
  • Algorithmic knowledge discovery
  • Factual data analysis
  • KDD (Information retrieval)
  • Knowledge discovery in data
  • Knowledge discovery in databases
  • Mining, Data
  • GNU-S (Computer program language)

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