Classifier training under stratified 10-fold cross validation. Because of the imbalance in positive/negative training examples we stratify on the label and ensure that each 10% of data held out as a test set contains equal proportions of both labels. Figure 6
(a) Relative feature importances averaged over the 10 CV folds. Figure 6
(b) Binomial deviance loss function plotted against model complexity for both the train and test splits of the data.