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
Introduction. Properties of Statistical Distributions. Important Matrix Relationships. Linear Modeling and Regression. Nonlinear Modeling. Time Series Analysis. Data Preparation and Variable Selection. Model Goodness Measures. Optimization Methods. Miscellaneous Topics. Appendices. Bibliography. Index.