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Decision Tree: ID3 algorithm: 1, Shannon entropy: If the transaction to be sorted may be divided into multiple classifications, then the information for x i is defined as:, where P (x i) chooses the probability of the classification. Entropy is defined as the expected value of information, and the calculation formula is: When the entropy is higher, the more data of different types, the higher the disorder o
The key points of the decision tree classification algorithm are: Which feature plays a key role, which is to divide the data according to which feature quantity. It is necessary to divide the data according to each characteristic quantity separately. The information gain of the divided data is calculated separately, and the corresponding characteristic quantity of the information gain is the selected char
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