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Data Mining for Business Analytics : Concepts, Techniques, and Applications in R by Peter C. Bruce, Kenneth C. Lichtendahl Jr., Galit Shmueli, Inbal Yahav and Nitin R. Patel (2017, Hardcover)

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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. It also includes: Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions www.dataminingbook.com 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. "This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject." Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1118879368
ISBN-13
9781118879368
eBay Product ID (ePID)
234971365

Product Key Features

Author
Nitin R. Patel, Inbal Yahav, Peter C. Bruce, Galit Shmueli, Kenneth C. Lichtendahl Jr.
Publication Name
Data Mining for Business Analytics : concepts, Techniques, and Applications in R
Format
Hardcover
Language
English
Subject
Probability & Statistics / General, Databases / Data Mining, Enterprise Applications / General, Business Mathematics
Publication Year
2017
Type
Textbook
Subject Area
Computers, Business & Economics, Mathematics
Number of Pages
576 Pages

Dimensions

Item Length
10.1 in
Item Height
1.2 in
Item Width
6.9 in
Item Weight
47.3 Oz

Additional Product Features

LCCN
2017-024503
Intended Audience
Scholarly & Professional
Lc Classification Number
Hf5548.2
Copyright Date
2018
Dewey Decimal
658.05
Dewey Edition
23
Illustrated
Yes

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item 1 Data Mining for Business - Hardcover, by Shmueli Galit; Bruce - Acceptable
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item 2 Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
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item 3 Data Mining for Business Intelligence: Concepts, Techniques, and Applicat - GOOD
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item 5 Data Mining for Business Analytics by Shumueli & Bruce INTERNATIONAL EDITION
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5 out of 5 stars
by cheze_59Nov 05, 2022
Heavy weight with some good features but should use color instead of B & W photos and include soft copies of problems in CD or other alternatives
Figures and tables should be in color not black & white. Materials for solving problems at the end of chapters should be in an enclosed CD or alternative soft copy source.
Verified purchase: Yes | Condition: Pre-owned

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