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Binding: HardcoverDewey Decimal Number: 006.312 EAN: 9780321321367 Edition: US ed ISBN: 0321321367 Label: Addison Wesley Manufacturer: Addison Wesley Number Of Items: 1 Number Of Pages: 769 Publication Date: May 12, 2005 Publisher: Addison Wesley Studio: Addison Wesley Editorial Review: Product Description: Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Average Rating:
 Rating: - I am very impressedI have never come across such a good book..it's so easy to read and sensible...can be a great introduction to phd studies..fun book to read Rating: - Great Machine Learning IntroductionThis is the book I used to introduce myself to data mining as graduate student in computer science. At the time I thought it was a very well organized and self contained book. Since then I have been studying machine learning full time and I still use this book to get really great explanations of key algorithms and concepts. Every time I go back to this book I'm surprised to find all sorts of topics covered that I hadn't noticed on previous readings. Basically it covers a good breadth of topics ... Read More Rating: - As an introduction, I love this bookIf you think you are interested in Data Mining this is a great place to start. This book would work well for people interested in self study, or someone who is considering going to grad school to pursue a field utilizing data mining, or doing data mining research directly. The book covers the core data mining concepts, with clear examples on how the concepts could be applied to toy problems. The book is light on math and heavy on application, which is great at maintaining interest. ... Read More Rating:  - very good introductionI agree with the other reviews: The book is amazingly well-written, and the two chapters on cluster analysis are second-to-none; Though I am particularly enthusiastic about this book, I believe that it cannot deserve 5 stars, for the following reasons: - Kernel methods: like most books on this subject, the authors do not explain how to choose the most appropriate kernel(s) - Cluster analysis: No examples of time-series - Fully worked-out real-world examples are missing ... Read More Rating: - Amazingly well written: simple, to the point, easy to read, and full useful informationThis book is amazingly well written. Everything is explained in a very clear and to-the-point style. The book can be read from front to back or used as a reference book. It contains countless diagrams and the structure of the content is immediately apparent. The book covers a lot of the important aspects of data mining. It provides algorithms and techniques for classification, clustering, association analysis, and anomaly detection. Every algorithm is not only formally stated, but also explained ... Read More |
