Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
The versatile capabilities and large set of add-on packages make R an excellent alternative to many existing and often expensive data mining tools. Get and download textbook Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) for free
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Exploring this area from the perspective of a practitioner, Data Mining with R: Learning with Case Studies uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, the book covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. To present the main data mining processes and techniques, the author takes a hands-on approach that utilizes a series of detailed, real-world case studies: Predicting algae blooms Predicting stock m Data Mining with R new edition
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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 va
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 va
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 va
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 va
Taylor & Francis Ltd | 2010 | 305 pages | ISBN-13: 9781439810187 | ISBN-10: 1439810184 | You save 10%
Data Mining with R : Hardback : Taylor & Francis Ltd : 9781439810187 : 1439810184 : 11 Nov 2010 : Provides a self-contained introduction to the use of R for exploratory data mining and machine learning. Employing a practical, learn-by-doing approach, this work presents a series of representative case studies from ecology, financial prediction, fraud detection, and bioinformatics, including all of the necessary steps, code, and data.
Data Mining with R Textbook
Exploring this area from the perspective of a practitioner, Data Mining with R: Learning with Case Studies uses practical examples to illustrate the power of R and data mining
To present the main data mining processes and techniques, the author takes a hands-on approach that utilizes a series of detailed, real-world case studies: Predicting algae blooms Predicting stock m
