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Foundations of predictive analytics

Author: James Wu; Stephen Coggeshall
Publisher: Boca Raton, FL : CRC Press, ©2012.
Series: Chapman & Hall/CRC data mining and knowledge discovery series.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Wu, James, 1965-
Foundations of predictive analytics.
Boca Raton, FL : CRC Press, ©2012
(DLC) 2011049779
(OCoLC)690089872
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James Wu; Stephen Coggeshall
ISBN: 9781439869482 1439869480
OCLC Number: 778497234
Description: 1 online resource (xix, 317 pages) : illustrations.
Contents: 1. Introduction --
2. Properties of statistical distributions --
3. Important matrix relationships --
4. Linear modeling and regression --
5. Nonlinear modeling --
6. Time series analysis --
7. Data preparation and variable selection --
8. Model goodness measures --
9. Optimization methods --
10. Miscellaneous topics.
Series Title: Chapman & Hall/CRC data mining and knowledge discovery series.
Responsibility: James Wu, Stephen Coggeshall.

Abstract:

"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"--

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"The book deals with the necessary knowledge for understanding the theoretical and practical aspects regarding the common techniques of exploratory data analysis and modeling. For a better Read more...

 
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