9781441998897-1441998896-Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)

Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)

ISBN-13: 9781441998897
ISBN-10: 1441998896
Edition: 2011
Author: Graham Williams
Publication date: 2011
Publisher: Springer
Format: Paperback 394 pages
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Book details

ISBN-13: 9781441998897
ISBN-10: 1441998896
Edition: 2011
Author: Graham Williams
Publication date: 2011
Publisher: Springer
Format: Paperback 394 pages

Summary

Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!) (ISBN-13: 9781441998897 and ISBN-10: 1441998896), written by authors Graham Williams, was published by Springer in 2011. With an overall rating of 3.9 stars, it's a notable title among other Data Mining (Databases & Big Data, Algorithms, Programming, Mathematical & Statistical, Software) books. You can easily purchase or rent Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!) (Paperback) from BooksRun, along with many other new and used Data Mining books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.32.

Description

Data Mining and Anlaytics are the foundation technologies for the new knowledge based world where we build models from data and databases to understand and explore our world. Data mining can improve our business, improve our government, and improve our life and with the right tools, any one can begin to explore this new technology, on the path to becoming a data mining professional. This book aims to get you into data mining quickly. Load some data (e.g., from a database) into the Rattle toolkit and within minutes you will have the data visualised and some models built. This is the first step in a journey to data mining and analytics. The book encourages the concept of programming by example and programming with data - more than just pushing data through tools, but learning to live and breathe the data, and sharing the experience so others can copy and build on what has gone before. It is accessible to many readers and not necessarily just those with strong backgrounds in computer science or statistics. Details of some of the more popular algorithms for data mining are very simply and, more importantly, clearly explained. Technology for transforming a database through data mining and machine learning into knowledge is now readily accessible.

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