Data Mining and Business Analytics with R#Johannes Ledolter

Data Mining and Business Analytics with R #368 pages #2013

#1118572157, 9781118572153 #Johannes Ledolter #John Wiley & Sons,

2013 #Showcases R's critical role in the world of business Collecting,

analyzing, and extracting valuable information from a large amount of

data requires easily accessible robust computational and analytical tools.

"Data Mining and Business Analytics with R" utilizes the open source

software R for the analysis, exploration, and simplification of large

high-dimensional data sets. As a result, readers are provided with the

needed guidance to model and interpret complicated data and become

adept at building powerful models for prediction and classification.

Highlighting both underlying concepts and practical computational skills,

"Data Mining and Business Analytics with R" begins with coverage of

standard linear regression and the importance of parsimony in statistical

modeling. The book includes important topics such as penalty-based

variable selection (LASSO); logistic regression; regression and

classification trees; clustering; principal components and partial least

squares; and the analysis of text and network data. In addition, the book

presents: A thorough discussion and extensive demonstration of the

theory behind the most useful data mining tools Illustrations of how to

use the outlined concepts in real-world situations Readily available

additional data sets and related R code allowing readers to apply their

own analyses to the discussed materials Numerous exercises to help

readers with computing skills and deepen their understanding of the

material "Data Mining and Business Analytics with R" is an excellent

graduate-level textbook for courses on data mining and business

analytics. The book is also a valuable reference for practitioners who

collect and analyze data in the fields of finance, operations management,

marketing, and the information sciences. file download lecira.pdf

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