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Decision tree algorithm is not only the important part of machine learning, but also the most widely used data mining tool. At present, there are many algorithms of generating decision tree, but when the database which we rely on exists noise, high quality knowledge is hard to obtain by ID3 algorithm. In this paper, we propose the data mining method based on second learning in case of ID3 algorithm,...
When noise exists in case base, high quality knowledge is hard to obtain by ID3 algorithm. For the weakness, by introducing the concept of second learning, the noisy data can be removed, which not only develop the decision tree, but also it can make good structure tree generate. So that we can abstract good rules information, and make the desirable tree more accurate. Especially, the more the data...
Induce learning is one of the most important research areas on application of artificial intelligence. The classification algorithm is the core of the machine learning. The article advanced a kind of decision classification algorithm that is in view of attribute value statistical regularity, on the characteristic and insufficient of ID3, C4.5 algorithm. (In short of BS-CA) This algorithm takes the...
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