Operates on streams of data, trained online or “live” on only a small amount of data kept in memory at a time, as opposed to the more classical approaches that are trained solely offline on all of the data at once. Each ensemble or stand-alone algorithm runs through a form of online supervised learning where each sample is tested and then trained on in sequence. Compares KNN/SVM/Hoeffding Adapative Trees/Adaptive Random Forests.