Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean/average prediction (regression) of the individual trees.
Random Forest is most likely to appear on Data Scientist job descriptions where we found it mentioned 5.8 percent of the time.