C4.5 Algorithm
The C4.5 Algorithm is the evolution of ID3 algorithm. It used a mechanism of learning. The attribute selection of algorithm is based on a assumption: the complexity of decision tree and the amount of information is represented by given attribute are closely linked. C4.5 expands the classify range to digital attribute. That metric standard of two-class entropy, the most of algorithm is based on the information entropy which is contained by produced nodal points of decision tree is least. The so called entropy is representative of degree of disorder of objects in the systematology. It is easy to understand that the smaller entropy the smaller disorder. In the other word the more sequential in the record collection, the more consistent. This is the target we seek, too. Suppose the set S is a training sample, the formula of entropy as follows:
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