Prerequisites: STAT 201A , STAT 201B, STAT 202A or equivalents; or consent of instructor
Description: Covers principle data-mining methodologies and applications. Includes Bayes and LDA classifiers, logistic regression and neural network classifiers, support vector classifiers, classification trees, predictive modeling, ridge and lasso regressions, k-means and Dendrogram clustering methods, business analytics and mining association rules. Features R and SAS programming language.