Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
John Wiley & Sons, 05.09.2017 - 576 Seiten
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:
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.
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Overview of the Data Mining Process
Evaluating Predictive Performance
kNearest Neighbors kNN
The Naive Bayes Classifier
Classification and Regression Trees
Association Rules and Collaborative Filtering
Handling Time Series
Social Network Analytics