Fig. 3

a Pictorial representation of a classification tree. b Diagram showing the steps for building a Random Forest (RF) classifier. c Graphical display of the prediction using RF for each localization. For each localization, 5 RF classifiers are built and the final prediction results are determined on the basis of majority voting scheme. Further, each RF classifier is trained with a balanced dataset that consists of all the positive instances and same number of randomly drawn negative instances. The negative dataset is different for all the five RF classifiers for every localizations