學習筆記，僅供參考，有錯必糾

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回歸樹與基于規則模型

基于規則的模型

A rule(規則) is de?ned as a distinct path through a tree(樹中一條不重復的路徑).For the
tree, a new sample can only travel down a single path through the tree de?ned by these rules.(對于一棵樹，新觀測只能沿著唯一的一條路徑由上至下，而路徑正是由一系列規則定義的) The number of samples a?ected by a rule is called its coverage.(被一條規則影響的觀測數，被稱為它的覆蓋)

Holmes等人構建了一種從模型樹中建立規則的方法，他們使用了"分而治之"的策略

This procedure derives rules from many di?erent model trees instead of from a single tree.
First, an initial model tree is created (they recommend using unsmoothed model trees). However, only the rule with the largest coverage is saved from this model. The samples covered by the rule are removed from the training set and another model tree is created with the remaining data. Again, only the rule with the maximum coverage is retained. This process repeats until all the training set data have been covered by at least one rule(被最后一條規則覆蓋). A new sample is predicted by determining which rule(s) it falls under then applies the linear model associated with the largest coverage(要預測新樣本時，首先將決定樣本落入了哪些規則之中，然后使用其中覆蓋最大的那條規則對應的線性模型進行預測).

總結

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