| W01-0715 | automatically combined in a decision | tree induction algorithm | . A detailed analysis of the |
| W01-0715 | testing . We use the C5 .0 Decision | Tree Induction Algorithm | ( Quinlan , 1992 ) . The baseline |
| D11-1064 | each of the folds . Note that the | tree induction algorithm | can also be used to construct |
| J97-2002 | same was true with the decision | tree induction algorithm | , as seen in Figure 4 . The lowest |
| P01-1055 | was replaced by the supervised | tree induction algorithm | C4 .5 ( Quinlan , 1993 ) , reaching |
| W00-1304 | contained in the node with a decision | tree induction algorithm | . The splitting criterion used |
| J06-3002 | ) . We use the C5 .0 Decision | Tree Induction Algorithm | ( Quinlan 1993 ) , and the implementation |
| W99-0611 | ample , apply the C4 .5 decision | tree induction algorithm | ( Quinlan , 1992 ) to the task |
| J14-4004 | greedy nature of the decision | tree induction algorithm | used in EFI and the variation |
| P99-1057 | Algorithms We used the C4 .5 decision | tree induction algorithm | ( Quinlan , 1993 ) and the backpropagation |
| J97-2002 | net . Integrating the decision | tree induction algorithm | into the Satz system was simply |
| J06-3002 | verb -- we use the C5 .0 Decision | Tree Induction Algorithm | ( Quinlan 1993 ) and Support |
| C00-2116 | .5 Learning Algorithm Decision | tree induction algorithms | have been successfully applied |
| E03-1079 | Settings We use the C5 .0 Decision | Tree Induction Algorithm | ( Quinlan , 1992 ) , applied |
| W99-0503 | were carried out using a decision | tree induction algorithm | , the C5 0 system available from |
