在机器学习中，随机森林是一个包含多个决策树的分类器， 并且其输出的类别是由个别树输出的类别的众数而定。 Leo Breiman和Adele Cutler发展出推论出随机森林的算法。 而 "Random Forests" 是他们的商标。 这个术语是1995年由贝尔实验室的Tin Kam Ho所提出的随机决策森林（random decision forests）而来的。这个方法则是结合 Breimans 的 "Bootstrap aggregating" 想法和 Ho 的"random subspace method"以建造决策树的集合。(In machine learning, random forest is a multiple decision tree classifier, and its output is composed of plural individual tree categories depending on the output category. Leo Breiman and Adele Cutler developed an algorithm to deduce a random forest. And "Random Forests" is their trademark. The term came from the random decision forest (random decision forests) proposed by Tin Kam Ho at Baer laboratory in 1995. This method is combined with the "Bootstrap aggregating" idea of Breimans and the "random subspace method" of Ho to build a set of decision trees.)