Description: C4.5 algorithm has the following advantages: the classification rules easier to understand, accurate and a higher rate. Its shortcomings are as follows: in the tree structure, the need for a number of data sets the order of scanning and sorting, thus leading to inefficient algorithms. In addition, C4.5 can only be applied to the presence of a data set in memory, when the training set too great to accommodate in memory when the program can not run.
- [imesample1] - A good input method sample for learning
- [C45Rule-PANE] - Description: C4.5Rule-PANE is a rule lea
- [DescionTree] - decision tree technology and C4.5 ID3 al
- [ID3C4.5] - ID3 C4.5 of the source. Data Mining for
- [c45] - C4.5 Classification Trees Induction Algo
- [dm1] - Prepared using java data mining algorith
- [c4.5java] - Decision tree classification algorithm,
- [DecisionTrees] - this is decision tree ID3 algorithm, thi
- [c45] - This is a data mining algorithm c4.5 cla
- [C4_5] - C4.5 Decision Tree code
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