Foundations of predictive analytics / James Wu, Stephen Coggeshall.

Format:

Book

Author/Creator:

Wu, James, 1965- author.

Contributor:

Coggeshall, Stephen.

Series:

Chapman & Hall/CRC data mining and knowledge discovery series.

Chapman & Hall/CRC data mining and knowledge discovery series

Language:

English

Subjects (All):

Data mining.

Predictive control--Mathematical models.

Predictive control.

Automatic control.

Physical Description:

1 online resource (335 p.)

Edition:

1st ed.

Place of Publication:

Boca Raton : CRC Press, 2012.

Boca Raton, Fla. : CRC Press, 2012.

Language Note:

English

Summary:

"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.

Contents:

Front Cover; Contents; List of Figures; List of Tables; Preface; 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; Appendix A: Useful Mathematical Relations; Appendix B: DataMinerXL - Microsoft Excel Add-In for Building Predictive Models; Bibliography

Notes:

"A Chapman & Hall book."

Includes bibliographical references.

Description based on metadata supplied by the publisher and other sources.

ISBN:

9786613909275

9781040162439

1040162436

9780429107351

0429107358

9781283596824

1283596822

9781439869482

1439869480

OCLC:

778497234