“… 2 Online learning methods, on the other hand, are restricted to the additive update of the weights of the ML model on new “online” training instances. A solution to this is to use incremental learning, 11 , 12 , 13 , 14 which trains a classifier on an initial database and then incrementally adjusts the weights of the classifier on a series of existing databases. Toward this direction, many incremental learning algorithms have been proposed, including the family of the multiple additive regression trees (MART), 14 , 15 , 16 the support vector machines (SVM), 17 , 18 and the multinomial naive Bayes, 14 where the gradient boosting trees (GBT) algorithm is the most popular implementation of MART with favorable performance in diverse classification tasks.…”