TY  - BOOK
AU  - Shmueli,Galit
AU  - Bruce,Peter C.
AU  - Yahav,Inbal
AU  - Patel,Nitin R.
AU  - Lichtendahl,Kenneth C.
TI  - Data mining for business analytics: concepts, techniques, and applications in R 
SN  - 9781118879368 
U1  - 006.312  23
PY  - 2018///
CY  - Hoboken, NJ : 
PB  - John Wiley & Sons
KW  - Business
KW  - Data processing
KW  - Data mining
KW  - R (Computer program language)
KW  - Business mathematics
KW  - Computer programs
N1  - Includes bibliographical references and index; Part I: Preliminaries --
Part II: Data exploration and dimension reduction --
Part III: Performance evaluation --
Part IV: Prediction and classification methods --
Part V: Mining relationships among records --
Part VI: Forecasting time series --
Part VII: Data analytics --
Part VIII: Cases
N2  - 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
ER  -