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Data mining for business analytics : concepts, techniques, and applications in R / Galit Shmueli, Peter C. Bruce, Inbal Yahav, Nitin R. Patel, Kenneth C. Lichtendahl, Jr.

By: Contributor(s): Material type: TextTextPublisher: Hoboken, NJ : John Wiley & Sons, Inc., 2018Copyright date: ©2018Description: xxix, 544 pages : illustrations ; 26 cm. ; casedISBN:
  • 9781118879368
  • 1118879368
  • 9781118879368
Subject(s): DDC classification:
  • 658.40380285 23
LOC classification:
  • .S55 2018
  • .S56 2018
Online resources:
Contents:
Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-Nearest Neighbors (kNN) -- The Naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Association rules and collaborative filtering -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Social network analytics -- Text mining -- Cases.
Holdings
Item type Current library Call number Status Date due Barcode
General Lending Carlow Campus Library General Lending 658.40380285 (Browse shelf(Opens below)) Checked out 31/08/2020 83655

95.90 CWB07

Includes bibliographical references (pages 531-532) and index.

Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-Nearest Neighbors (kNN) -- The Naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Association rules and collaborative filtering -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Social network analytics -- Text mining -- Cases.

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