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This paper analyzes the existing decision tree classification algorithms and finds that these algorithms based on variable precision rough set (VPRS) have better classification accuracies and can tolerate the noise data. But when constructing decision tree based on variable precision rough set, these algorithms have the following shortcomings: the choice of attribute is difficult and the decision...
This paper analyzes the existing decision tree classification algorithms based on variable precision rough set and finds that these algorithms have better classification accuracies and can tolerate the noise data. But when choosing the best attribute using variable precision rough set, these algorithms still have the shortages in ID3. That is, these algorithms also tend to choose the attribute with...
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