Data Mining with Rattle and R
The Art of Excavating Data for Knowledge Discovery
Book Details:
Pages: | 374 |
Published: | Aug 04 2011 |
Posted: | Nov 19 2014 |
Language: | English |
Book format: | PDF |
Book size: | 10.92 MB |
Book 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.
Develop key skills and techniques with R to create and customize data mining algorithms About This BookDevelop a sound strategy for solving predictive modeling problems using the most popular data mining algorithmsGain understanding of the major methods of predictive modelingPacked with practical advice and tips to help you get to grips with data miningWho This Book Is ForThis book is intended for the budding data scientist or quantitative analyst with only a basic exposure to R and statistics. This book assumes familiarity with only the very basics of R, such as the main data types, simple functions, and how to move data around. No prior experience with data mining packages is necessary; however, you should have a basic understanding of data mining ...
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