Random Forest (page 1 of 5)

The random forest algorithm is a supervised machine learning algorithm. It can be used to solve both regression (continuous known targets) and classification (categorical known targets) problems. The random forest algorithm produces an ensemble model (i.e., a collection of many decision tree models). That is, a trained random forest model consists of many decision trees. The prediction is made by the collection of trees in the ensemble random forest. Therefore, the model is a "blackbox" model for decision makers because the details behind each tree are unknown to them.