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Field name	Details
Dewey Class	519.5
Title	Data Mining with Rattle and R ([Ebook]) : The Art of Excavating Data for Knowledge Discovery / by Graham Williams.
Author	Williams, Graham
Other name(s)	SpringerLink (Online service)
Publication	New York, NY : Springer , 2011.
Physical Details	XX, 374 pages:. 95 illus., 80 illus. in color. : online resource.
Series	Use R
ISBN	9781441998903
Summary Note	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,Â 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.:
Contents note	Introduction -- Getting Started -- Working with Data -- Loading Data -- Exploring Data -- Interactive Graphics -- Transforming Data -- Descriptive and Predictive Analytics -- Cluster Analysis -- Association Analysis -- Decision Trees -- Random Forests -- Boosting -- Support Vector Machines -- Model Performance Evaluation -- Deployment.
System details note	Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site	http://dx.doi.org/10.1007/978-1-4419-9890-3
Links to Related Works	Subject References: Statistics . Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences . Authors: Williams, Graham . Corporate Authors: SpringerLink (Online service) . Series: Use R . Classification: 519.5 . 519.5 (DDC 22) .

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Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery /

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