Decision stump

A decision stump makes a prediction based on the value of just a single input feature.

For nominal features, one may build a stump which contains a leaf for each possible feature value[3][4] or a stump with the two leaves, one of which corresponds to some chosen category, and the other leaf to all the other categories.

However, rarely, multiple thresholds may be chosen and the stump therefore contains three or more leaves.

For example, a Viola–Jones face detection algorithm employs AdaBoost with decision stumps as weak learners.

[7] The term "decision stump" was coined in a 1992 ICML paper by Wayne Iba and Pat Langley.

An example of a decision stump that discriminates between two of three classes of Iris flower data set : Iris versicolor and Iris virginica . The petal width is in centimetres. This particular stump achieves 94% accuracy on the Iris dataset for these two classes.