A decision stump is a decision tree with just one decision, leading to two or more leaves. For example, in this decision stump a borrower score of 0.475 or greater leads to a classification of “loan will default” while a borrower score less than 0.475 leads to a classification of “loan will be paid off”:

Decision stumps, a form of “weak learner,” are used in ensemble methods – they are combined together to yield more accurate predictions than they make on their own.