Nonelinear Model
Decision Tree
- decision tree is a supervised prediction model
it is usually a k-nary tree. each leaf denotes one classification or continuous value of the dependent variable. - two types of dependent variable:
- classification tree
- regression tree
- how to build a decision tree:
- two steps:
feature prioritization
feature splitting - Algorithnm Details - ID3 Algorithm
at each iteration step, we split the feature which can give us the largest entropy gain 直观理解:减少偏见
Definition of Entropy: Entropy of the entire information system:
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- two steps:
- other tree algortithms:
- C4.5 Algorithm: Gain Rate
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CART: Gini impurity
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