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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
Data Mining for Business Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustrationReaders 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
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
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
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
997 pages, Kindle Edition
Published January 7, 2023
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April 7, 2024
text book for data mining course at Bentley University.
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