Data Mining with Rattle and R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining with Rattle and R write by Graham Williams. This book was released on 2011-08-04. Data Mining with Rattle and R available in PDF, EPUB and Kindle. Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.
Data Mining with Rattle and R
Data Mining with Rattle and R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining with Rattle and R write by . This book was released on 2011-08-03. Data Mining with Rattle and R available in PDF, EPUB and Kindle.
Educational Data Mining with R and Rattle
Educational Data Mining with R and Rattle - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Educational Data Mining with R and Rattle write by R. S. Kamath. This book was released on 2016. Educational Data Mining with R and Rattle available in PDF, EPUB and Kindle. It includes the transformation of existing, and the innovation of new approaches derived from multidisciplinary spheres of influence such as statistics, machine learning, psychometrics, scientific computing etc.An archetype that is covered in this book is that of learning by example.
Data Mining and Business Analytics with R
Data Mining and Business Analytics with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Business Analytics with R write by Johannes Ledolter. This book was released on 2013-05-28. Data Mining and Business Analytics with R available in PDF, EPUB and Kindle. 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.
R and Data Mining
R and Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook R and Data Mining write by Yanchang Zhao. This book was released on 2012-12-31. R and Data Mining available in PDF, EPUB and Kindle. R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. Presents an introduction into using R for data mining applications, covering most popular data mining techniques Provides code examples and data so that readers can easily learn the techniques Features case studies in real-world applications to help readers apply the techniques in their work
