Algorithms Used Sample Clauses

Algorithms Used. We use Adaboost to create the original ensemble for pruning. Following Xxxxx et al. (2006) the ensemble size was set to one hundred. If the training error converges to zero before the ensemble sizes reaches one hundred, then all the subsequent members will be replications of the last member because no instance weight is changed. Therefore in such cases, the AdaBoost.M1 procedure is repeated using a different random seed. Note that the original AdaBoost weights are used to weight the predictions of the selected members. As for the induction algorithm that was used for training the base classifier, we have examined the C4.5 decision tree algorithm (Xxxxxxx, 1993) and decision xxxxx. The C4.5 algorithm is frequently used for comparing ensembles. Decision xxxxx is a weak learner consisting of a one-level tree which known to be benefit from boosting strategy (Xxxxxxxxxx et al., 2006). The new algorithm is compared to the following ensemble pruning methods:
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Related to Algorithms Used

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