Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A decision stump is a machine learning model consisting of a one-level decision tree. That is, it is a decision tree with one internal node (the root) which is immediately connected to the terminal nodes. A decision stump makes a prediction based on the value of just a single input feature. Depending on the type of the input feature, several variations are possible. For nominal features, one may build a stump which contains a leaf for each possible feature value (such classifiers have sometimes been also called "1-rules") or a stump with the two leaves, one of which corresponds to some chosen category, and the other leaf to all the other categories.

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