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Learning Data Mining with R by Bater Makhabel

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Web spam detection using C4.5

C4.5 is an extension of ID3. The major extensions include handling data with missing attribute values, and handling attributes that belong to an infinite continuous range.

It is one of the decision tree algorithms, and is also a supervised learning classification algorithm. A model is learned and the input attribute values are mapped to the mutually exclusive class labels. Moreover, the learned model will be used to further classify new unseen instances or attribute values. The attribute select measure adopted in C4.5 is the gain ratio, which avoids the possible bias:

Web spam detection using C4.5

Based on the generic C4.5 algorithm, a suite for varieties ...

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