Data Mining and Business Analytics with R by Johannes Ledolter

Data Mining and Business Analytics with R by Johannes Ledolter affords thorough dialogue and in depth demonstration of the idea behind essentially the most helpful information mining tools. There are illustrations of the best way to use the outlined concepts in actual-world situations. There are readily available additional knowledge units and associated R code permitting readers to apply their very own analyses to the mentioned materials.

Gathering, analyzing, and extracting precious information from a considerable amount of knowledge requires easily accessible, sturdy, computational and analytical tools. It utilizes the open source software R for the analysis, exploration, and simplification of large excessive-dimensional information sets. As a result, readers are provided with the wanted guidance to mannequin and interpret sophisticated information and turn into adept at building powerful models for prediction and classification.

Highlighting underlying ideas and practical computational expertise, this book begins with coverage of ordinary linear regression and the significance of parsimony in statistical modeling. The book includes necessary subjects comparable to penalty-based mostly variable choice (LASSO); logistic regression; regression and classification timber; clustering; principal elements and partial least squares; and the analysis of text and network data.

The early chapters review traditional regression and logistic regression models with applications on Monetary Economics. Then the book moves shortly to lesser identified techniques which can be significantly useful for dealing with massive data sets. These methods embrace nearest neighbor analysis, Bayesian analysis, regression and classification trees, clustering, and market basket analysis. The book ends with a complete set of exercises.

The last eight of the workout routines are notably priceless as a result of they provide detailed labored examples and in various cases embody different statistical approaches to the same problem. The entire final workout routines are tied to the book's chapters, whereas all examples and exercises make use of the powerful and free R Statistical Software. The whole R code is available on the book and author netsites.

Quite a few workout routines assist readers with computing abilities and deepen their understanding of the material. It's an excellent graduate-level textbook for programs on knowledge mining and business analytics. The book can also be invaluable reference for practitioners who collect and analyze information in the fields of finance, operations management, marketing, and the information sciences.

Book Details

Hardcover: 368 pages
Publisher: Wiley; 1 edition (May 28, 2013)
Language: English
ISBN-10: 111844714X

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