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192.168.6.56/handle/123456789/88767| Title: | Principles of Data Mining |
| Authors: | Samson Abramsky, Karin Breitman, Chris Hankin, Dexter Kozen, Andrew Pitts, Hanne Riis Nielson, Steven Skiena and Iain Stewart Hannu, Karttu Ian Mackie |
| Keywords: | Principles of Data Mining |
| Issue Date: | 2016 |
| Publisher: | Springer Science+Business Media, LLC 2010 |
| Description: | This book is designed to be suitable for an introductory course at either un- dergraduate or masters level. It can be used as a textbook for a taught unit in a degree programme on potentially any of a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioin- formatics and Forensic Science. It is also suitable for use as a self-study book for those in technical or management positions who wish to gain an understanding of the subject that goes beyond the superficial. It goes well beyond the gener- alities of many introductory books on Data Mining but—unlike many other books—you will not need a degree and/or considerable fluency in Mathematics to understand it. |
| URI: | http://196.189.45.87:8080/handle/123456789/88767 |
| ISBN: | 978-1-4471-7307-6 |
| Appears in Collections: | Computer Science |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2016_Book_PrinciplesOfDataMining.pdf | 3.95 MB | Adobe PDF | View/Open |
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