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 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 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 governmentUpdates and new material based on feedback from instructors teaching MBA undergraduate diploma and executive courses and from their studentsMore than a dozen case studies demonstrating applications for the data mining techniques describedEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presentedA companion website with more than two dozen data sets and instructor materials including exercise solutions PowerPoint slides and case solutions� www.dataminingbook.comData 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.Read more
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