Feature and Model Selection

1 credits

Performance of a classification model. Generalization error, overfitting of training data. Shrinkage, feature selection, Akaike Information Criterion, Bayesian Information Criterion. k-fold cross validation. Bootstrapping. Receiver Operating Characteristic curve. Elastic nets, regularization. Prerequisite: DSCI_V 571. This course is not eligible for Credit/D/Fail grading.