Random forests: from early developments to recent advancements

Ensemble classification is a data mining approach that utilizes a number of classifiers that work together in order to identify the class label for unlabeled instances. Random forest (RF) is an ensemble classification approach that has proved its high accuracy and superiority. With one common goal in mind, RF has recently received considerable attention from the research community to further boost its performance. In this paper, we look at developments of RF from birth to present. The main aim is to describe the research done to date and also identify potential and future developments to RF. Our approach in this review paper is to take a historical view on the development of this notably successful…