Data Mining and Business Analytics with R

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Data Mining and Business Analytics with R by Johannes Ledolter, Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Johannes Ledolter ISBN: 9781118572153
Publisher: Wiley Publication: May 28, 2013
Imprint: Wiley Language: English
Author: Johannes Ledolter
ISBN: 9781118572153
Publisher: Wiley
Publication: May 28, 2013
Imprint: Wiley
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Wiley

Cover of the book Rapid Surgery by Johannes Ledolter
Cover of the book Handbook of Practical Program Evaluation by Johannes Ledolter
Cover of the book Evidence-Based Medicine Toolkit by Johannes Ledolter
Cover of the book The SketchUp Workflow for Architecture by Johannes Ledolter
Cover of the book Java für die Android-Entwicklung für Dummies by Johannes Ledolter
Cover of the book From GSM to LTE-Advanced Pro and 5G by Johannes Ledolter
Cover of the book Mine Ventilation and Air Conditioning by Johannes Ledolter
Cover of the book Wiley Practitioner's Guide to GAAS 2010 by Johannes Ledolter
Cover of the book LTE-Advanced and Next Generation Wireless Networks by Johannes Ledolter
Cover of the book Building Better Teams by Johannes Ledolter
Cover of the book High Performance Polymers and Their Nanocomposites by Johannes Ledolter
Cover of the book My Life as a Quant by Johannes Ledolter
Cover of the book Natural Gas by Johannes Ledolter
Cover of the book Food Industry R&D by Johannes Ledolter
Cover of the book Sports Research with Analytical Solution using SPSS by Johannes Ledolter
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy