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1. Decision stumps的概念
http://www.answers.com/topic/decision-stump
A decision stump is a machine learning model consisting of a one-leveldecision tree.[1] 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. Sometimes they are also called1-rules.[2]
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[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.[5] For binary features these two schemes are identical. A missing value may be treated as a yet another category.[5]
For continuous features, usually, some threshold feature value is selected, and the stump contains two leaves — for values below and above the threshold. However, rarely, multiple thresholds may be chosen and the stump therefore contains three or more leaves.
Decision stumps are often
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