This course will introduce the basics of predictive modeling (“classifier construction”). We will discuss some of the most common types of classifiers, such as classification trees, random forests, support vector machines, discriminant analysis and K-nearest neighbor classifiers. We will also discuss measures and strategies for evaluating the performance of a classifier appropriately using cross-validation.