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Handbook of Statistical Analysis and Data Mining Applications [With DVD]
by Nisbet, Robert; Elder, John; Miner,... | HC | Good
US $6.59
Approximately£4.96
Condition:
“Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, ”... Read moreAbout condition
Good
A book that has been read, but is in good condition. Minimal damage to the book cover eg. scuff marks, but no holes or tears. If this is a hard cover, the dust jacket may be missing. Binding has minimal wear. The majority of pages are undamaged with some creasing or tearing, and pencil underlining of text, but this is minimal. No highlighting of text, no writing in the margins, and no missing pages. See the seller’s listing for full details and description of any imperfections.
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eBay item number:145140015181
Item specifics
- Condition
- Good
- Seller notes
- Binding
- Hardcover
- Weight
- 3 lbs
- Product Group
- Book
- IsTextBook
- Yes
- ISBN
- 0123747651
- Publication Year
- 2009
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Subject Area
- Mathematics, Computers
- Publication Name
- Handbook of Statistical Analysis and Data Mining Applications
- Publisher
- Elsevier Science & Technology
- Item Length
- 9.2 in
- Subject
- Probability & Statistics / General, Probability & Statistics / Multivariate Analysis, Databases / Data Mining
- Item Width
- 7.5 in
- Number of Pages
- 864 Pages
About this product
Product Identifiers
Publisher
Elsevier Science & Technology
ISBN-10
0123747651
ISBN-13
9780123747655
eBay Product ID (ePID)
71135175
Product Key Features
Number of Pages
864 Pages
Publication Name
Handbook of Statistical Analysis and Data Mining Applications
Language
English
Publication Year
2009
Subject
Probability & Statistics / General, Probability & Statistics / Multivariate Analysis, Databases / Data Mining
Type
Textbook
Subject Area
Mathematics, Computers
Format
Hardcover
Dimensions
Item Length
9.2 in
Item Width
7.5 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2009-008997
Reviews
"...If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner." - Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World "Great introduction to the real-world process of data mining. The overviews, practical advice, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners." -- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts), Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners.' - Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts) If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner. - Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World|9780123747655|, "Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners." - Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts) If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner. - Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World, Data mining practitioners, here is your bible, the complete "driver's manual" for data mining. From starting the engine to handling the curves, this book covers the gamut of data mining techniques - including predictive analytics and text mining - illustrating how to achieve maximal value across business, scientific, engineering and medical applications. What are the best practices through each phase of a data mining project? How can you avoid the most treacherous pitfalls? The answers are in here. Going beyond its responsibility as a reference book, this resource also provides detailed tutorials with step-by-step instructions to drive established data mining software tools across real world applications. This way, newcomers start their engines immediately and experience hands-on success. If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner. - Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World "Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners." -- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
006.3/12
Table Of Content
Preface Forwards Introduction PART I: History of Phases of Data Analysis, Basic Theory, and the Data Mining Process Chapter 1. History - The Phases of Data Analysis throughout the Ages Chapter 2. Theory Chapter 3. The Data Mining Process Chapter 4. Data Understanding and Preparation Chapter 5. Feature Selection - Selecting the Best Variables Chapter 6: Accessory Tools and Advanced Features in Data PART II: - The Algorithms in Data Mining and Text Mining, and the Organization of the Three most common Data Mining Tools Chapter 7. Basic Algorithms Chapter 8: Advanced Algorithms Chapter 9. Text Mining Chapter 10. Organization of 3 Leading Data Mining Tools Chapter 11. Classification Trees = Decision Trees Chapter 12. Numerical Prediction (Neural Nets and GLM Chapter 13. Model Evaluation and Enhancement Chapter 14. Medical Informatics Chapter 15. Bioinformatics Chapter 16. Customer Response Models Chapter 17. Fraud Detection PART III: Tutorials - Step-by-Step Case Studies as a Starting Point to learn how to do Data Mining Analyses Tutorials PART IV: Paradox of Complex Models; using the "right model for the right use", on-going development, and the Future. Chapter 18: Paradox of Ensembles and Complexity Chapter 19: The Right Model for the Right Use Chapter 20: The Top 10 Data Mining Mistakes Chapter 21: Prospect for the Future - Developing Areas in Data Mining Chapter 22: Summary GLOSSARY of STATISICAL and DATA MINING TERMS INDEX CD - With Additional Tutorials, data sets, Power Points, and Data Mining software
Synopsis
The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions., The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. Written "By Practitioners for Practitioners" Non-technical explanations build understanding without jargon and equations Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models Practical advice from successful real-world implementations Includes extensive case studies, examples, MS PowerPoint slides and datasets CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book
LC Classification Number
QA76.9.D343
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