Foundations of predictive analytics
(eBook)
Author
Contributors
Published
Boca Raton : CRC Press, 2012.
Physical Desc
xix, 312 pages : ill.
Status
More Details
Format
eBook
Language
English
Notes
Bibliography
Includes bibliographical references.
Description
"Preface this text is a summary of techniques of data analysis and modeling that the authors have encountered and used in our two-decades experience of practicing the art of applied data mining across many different fields. The authors have worked in this field together and separately in many large and small companies, including the Los Alamos National Laboratory, Bank One (JPMorgan Chase), Morgan Stanley, and the startups of the Center for Adaptive Systems Applications (CASA), the Los Alamos Computational Group and ID Analytics. We have applied these techniques to traditional and nontraditional problems in a wide range of areas including consumer behavior modeling (credit, fraud, marketing), consumer products, stock forecasting, fund analysis, asset allocation, and equity and xed income options pricing. This monograph provides the necessary information for understanding the common techniques for exploratory data analysis and modeling. It also explains the details of the algorithms behind these techniques, including underlying assumptions and mathematical formulations. It is the authors' opinion that in order to apply di erent techniques to di erent problems appropriately, it is essential to understand the assumptions and theory behind each technique. It is recognized that this work is far from a complete treatise on the subject. Many excellent additional texts exist on the popular subjects and it was not a goal for this present text to be a complete compilation. Rather this text contains various discussions on many practical subjects that are frequently missing from other texts, as well as details on some subjects that are not often or easily found. Thus this text makes an excellent supplemental and referential resource for the practitioners of these subjects"--,Provided by publisher.
Reproduction
Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
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Citations
APA Citation, 7th Edition (style guide)
Wu, J., & Coggeshall, S. (2012). Foundations of predictive analytics . CRC Press.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Wu, James, 1965- and Stephen. Coggeshall. 2012. Foundations of Predictive Analytics. CRC Press.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Wu, James, 1965- and Stephen. Coggeshall. Foundations of Predictive Analytics CRC Press, 2012.
MLA Citation, 9th Edition (style guide)Wu, James, and Stephen Coggeshall. Foundations of Predictive Analytics CRC Press, 2012.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
Staff View
Grouped Work ID
1f62c253-a29e-7458-016b-c1bcee35846a-eng
Grouping Information
| Grouped Work ID | 1f62c253-a29e-7458-016b-c1bcee35846a-eng |
|---|---|
| Full title | foundations of predictive analytics |
| Author | wu james |
| Grouping Category | book |
| Last Update | 2022-06-07 21:23:19PM |
| Last Indexed | 2024-04-17 02:36:04AM |
Book Cover Information
| Image Source | default |
|---|---|
| First Loaded | Aug 10, 2022 |
| Last Used | Apr 1, 2024 |
Marc Record
| First Detected | Aug 09, 2021 01:56:33 PM |
|---|---|
| Last File Modification Time | Nov 22, 2021 09:57:18 AM |
MARC Record
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| 245 | 1 | 0 | |a Foundations of predictive analytics|h [eBook] /|c James Wu, Stephen Coggeshall. |
| 260 | |a Boca Raton :|b CRC Press,|c 2012. | ||
| 300 | |a xix, 312 p. :|b ill. | ||
| 490 | 1 | |a Chapman & Hall/CRC data mining and knowledge discovery series | |
| 504 | |a Includes bibliographical references. | ||
| 520 | |a "Preface this text is a summary of techniques of data analysis and modeling that the authors have encountered and used in our two-decades experience of practicing the art of applied data mining across many different fields. The authors have worked in this field together and separately in many large and small companies, including the Los Alamos National Laboratory, Bank One (JPMorgan Chase), Morgan Stanley, and the startups of the Center for Adaptive Systems Applications (CASA), the Los Alamos Computational Group and ID Analytics. We have applied these techniques to traditional and nontraditional problems in a wide range of areas including consumer behavior modeling (credit, fraud, marketing), consumer products, stock forecasting, fund analysis, asset allocation, and equity and xed income options pricing. This monograph provides the necessary information for understanding the common techniques for exploratory data analysis and modeling. It also explains the details of the algorithms behind these techniques, including underlying assumptions and mathematical formulations. It is the authors' opinion that in order to apply di erent techniques to di erent problems appropriately, it is essential to understand the assumptions and theory behind each technique. It is recognized that this work is far from a complete treatise on the subject. Many excellent additional texts exist on the popular subjects and it was not a goal for this present text to be a complete compilation. Rather this text contains various discussions on many practical subjects that are frequently missing from other texts, as well as details on some subjects that are not often or easily found. Thus this text makes an excellent supplemental and referential resource for the practitioners of these subjects"--|c Provided by publisher. | ||
| 533 | |a Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Predictive control|x Mathematical models. | |
| 650 | 0 | |a Automatic control. | |
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Coggeshall, Stephen. | |
| 710 | 2 | |a ProQuest (Firm) | |
| 830 | 0 | |a Chapman & Hall/CRC data mining and knowledge discovery series. | |
| 856 | 4 | 0 | |u http://ebookcentral.proquest.com/lib/yavapai-ebooks/detail.action?docID=870690|x Yavapai College|y Yavapai College users click here to access |
| 856 | 4 | 0 | |u http://ebookcentral.proquest.com/lib/prescottcollege-ebooks/detail.action?docID=870690|x Prescott College|y Prescott College users click here to access |
| 856 | 4 | 0 | |u http://ebookcentral.proquest.com/lib/yln-ebooks/detail.action?docID=870690|x Yavapai Library Network|y All other users click here to access |
| 945 | |a E-Book | ||
