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Chapter 1 - Introduction
Pages 1-22 - Book chapterAbstract only
Chapter 2 - Probability and Statistics
Pages 23-53 - Book chapterAbstract only
Chapter 3 - Artificial Neural Networks
Pages 54-86 - Book chapterAbstract only
Chapter 4 - Support Vector Machines
Pages 87-110 - Book chapterAbstract only
Chapter 5 - Decision Trees
Pages 111-138 - Book chapterAbstract only
Chapter 6 - Bayesian Classification
Pages 139-190 - Book chapterAbstract only
Chapter 7 - Cluster Analysis
Pages 191-237 - Book chapterAbstract only
Chapter 8 - Kriging
Pages 238-274 - Book chapterAbstract only
Chapter 9 - Other Soft Computing Algorithms for Geosciences
Pages 275-319 - Book chapterAbstract only
Chapter 10 - A Practical Software System of Data Mining and Knowledge Discovery for Geosciences
Pages 320-340 - Book chapterNo access
Appendix 1 - Table of Unit Conversion
Pages 341-344 - Book chapterNo access
Appendix 2 - Answers to Exercises
Pages 345-360 - Book chapterNo access
Index
Pages 361-367
About the book
Description
Currently there are major challenges in data mining applications in the geosciences. This is due primarily to the fact that there is a wealth of available mining data amid an absence of the knowledge and expertise necessary to analyze and accurately interpret the same data. Most geoscientists have no practical knowledge or experience using data mining techniques. For the few that do, they typically lack expertise in using data mining software and in selecting the most appropriate algorithms for a given application. This leads to a paradoxical scenario of "rich data but poor knowledge".
The true solution is to apply data mining techniques in geosciences databases and to modify these techniques for practical applications. Authored by a global thought leader in data mining, Data Mining and Knowledge Discovery for Geoscientists addresses these challenges by summarizing the latest developments in geosciences data mining and arming scientists with the ability to apply key concepts to effectively analyze and interpret vast amounts of critical information.
Currently there are major challenges in data mining applications in the geosciences. This is due primarily to the fact that there is a wealth of available mining data amid an absence of the knowledge and expertise necessary to analyze and accurately interpret the same data. Most geoscientists have no practical knowledge or experience using data mining techniques. For the few that do, they typically lack expertise in using data mining software and in selecting the most appropriate algorithms for a given application. This leads to a paradoxical scenario of "rich data but poor knowledge".
The true solution is to apply data mining techniques in geosciences databases and to modify these techniques for practical applications. Authored by a global thought leader in data mining, Data Mining and Knowledge Discovery for Geoscientists addresses these challenges by summarizing the latest developments in geosciences data mining and arming scientists with the ability to apply key concepts to effectively analyze and interpret vast amounts of critical information.
Key Features
- Focuses on 22 of data mining’s most practical algorithms and popular application samples
- Features 36 case studies and end-of-chapter exercises unique to the geosciences to underscore key data mining applications
- Presents a practical and integrated system of data mining and knowledge discovery for geoscientists
- Rigorous yet broadly accessible to geoscientists, engineers, researchers and programmers in data mining
- Introduces widely used algorithms, their basic principles and conditions of applications, diverse case studies, and suggests algorithms that may be suitable for specific applications
- Focuses on 22 of data mining’s most practical algorithms and popular application samples
- Features 36 case studies and end-of-chapter exercises unique to the geosciences to underscore key data mining applications
- Presents a practical and integrated system of data mining and knowledge discovery for geoscientists
- Rigorous yet broadly accessible to geoscientists, engineers, researchers and programmers in data mining
- Introduces widely used algorithms, their basic principles and conditions of applications, diverse case studies, and suggests algorithms that may be suitable for specific applications
Details
ISBN
978-0-12-410437-2
Language
English
Published
2014
Copyright
Copyright © 2014 Elsevier Inc. All rights reserved.
Imprint
Elsevier