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Data Mining Concepts and Techniques (3rd ED)
Publisher:
Morgan kaufmann Publishers
| Author:
Jiawei han, Micheline kamber, Jian Pei
| Language:
English
| Format:
Paperback
Publisher:
Morgan kaufmann Publishers
Author:
Jiawei han, Micheline kamber, Jian Pei
Language:
English
Format:
Paperback
₹725 ₹363
Save: 50%
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No pen or pencil marks |
ISBN:
Category: Computer Engineering/IT Engineering
Page Extent:
744
Data mining is the task of extracting precious information from masses of raw data. The results of data mining could find many different uses and more and more companies are investing in this technology. Data Mining: Concepts And Techniques (The Morgan Kaufmann Series In Data Management Systems) explains all the fundamental tools and techniques involved in the process and also goes into many advanced techniques.
This book not only introduces the fundamentals of data mining, it also explores new and emerging tools and techniques. It explains basic data mining concepts like OLAP, concept description, data preprocessing, classification and prediction, association rules and cluster analysis. It then presents advanced data mining techniques like extracting information from varied and complex sources other than just relational databases. This includes multimedia databases, object databases, time-series databases and spatial databases. It also looks at harvesting data from varied sources on the world wide web and extracting useful information from it.
Data Mining: Concepts And Techniques (The Morgan Kaufmann Series in Data Management Systems) is arranged in such way that the chapters stand as independent units. This makes it flexible as a classroom material, as instructors can choose the chapters they want and present the lessons in the order they prefer.
This third revised edition of the book was brought out by Morgan Kaufmann Publishers In in 2011 in hardcover.
Key Features:
Numerous algorithms are presented in pseudo code that can be can be applied in real world projects.
A number of pedagogical resources ae available for instructors in the companion website.
Be the first to review “Data Mining Concepts and Techniques (3rd ED)” Cancel reply
Description
Data mining is the task of extracting precious information from masses of raw data. The results of data mining could find many different uses and more and more companies are investing in this technology. Data Mining: Concepts And Techniques (The Morgan Kaufmann Series In Data Management Systems) explains all the fundamental tools and techniques involved in the process and also goes into many advanced techniques.
This book not only introduces the fundamentals of data mining, it also explores new and emerging tools and techniques. It explains basic data mining concepts like OLAP, concept description, data preprocessing, classification and prediction, association rules and cluster analysis. It then presents advanced data mining techniques like extracting information from varied and complex sources other than just relational databases. This includes multimedia databases, object databases, time-series databases and spatial databases. It also looks at harvesting data from varied sources on the world wide web and extracting useful information from it.
Data Mining: Concepts And Techniques (The Morgan Kaufmann Series in Data Management Systems) is arranged in such way that the chapters stand as independent units. This makes it flexible as a classroom material, as instructors can choose the chapters they want and present the lessons in the order they prefer.
This third revised edition of the book was brought out by Morgan Kaufmann Publishers In in 2011 in hardcover.
Key Features:
Numerous algorithms are presented in pseudo code that can be can be applied in real world projects.
A number of pedagogical resources ae available for instructors in the companion website.
About Author
"A well-written textbook (2nd ed., 2006; 1st ed., 2001) on data mining or knowledge discovery. The text is supported by a strong outline. The authors preserve much of the introductory material, but add the latest techniques and developments in data mining, thus making this a comprehensive resource for both beginners and practitioners. The focus is data―all aspects. The presentation is broad, encyclopedic, and comprehensive, with ample references for interested readers to pursue in-depth research on any technique. Summing Up: Highly recommended. Upper-division undergraduates through professionals/practitioners." --CHOICE
"This interesting and comprehensive introduction to data mining emphasizes the interest in multidimensional data mining--the integration of online analytical processing (OLAP) and data mining. Some chapters cover basic methods, and others focus on advanced techniques. The structure, along with the didactic presentation, makes the book suitable for both beginners and specialized readers.
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