 |
STATS315B |
 |
Modern Applied Statistics: Data Mining |
 |
2-3 |
 |
Friedman Jerome H |
This is the second course in two-part sequence. This course covers new techniques for predictive and descriptive learning using ideas that bridge gaps among statistics, computer science, and artificial intelligence. Predictive learning refers to estimating models from data with the goal of predicting future outcomes, in particular, regression and classification models. Descriptive learning is used to discover general patterns and relationships in data without a predictive goal, viewed from a statistical perspective as computer automated exploratory analysis of large complex data sets.