|
" Foundations of Predictive Analytics. "
James Wu
| Document Type
|
:
|
BL
|
| Record Number
|
:
|
733879
|
| Doc. No
|
:
|
b553702
|
| Main Entry
|
:
|
James Wu
|
| Title & Author
|
:
|
Foundations of Predictive Analytics.\ James Wu
|
| Publication Statement
|
:
|
Hoboken: CRC Press, 2012
|
| Series Statement
|
:
|
Chapman & Hall/CRC data mining and knowledge discovery series.
|
| Page. NO
|
:
|
(335 pages).
|
| ISBN
|
:
|
1439869480
|
|
|
:
|
: 9781439869482
|
| 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
|
| Abstract
|
:
|
Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish--Fisher expansion and o.
|
| Subject
|
:
|
Automatic control.
|
| Subject
|
:
|
Data mining.
|
| Subject
|
:
|
Predictive control -- Mathematical models.
|
| LC Classification
|
:
|
QA76.9.D343J364 2012
|
| Added Entry
|
:
|
James Wu
|
| |