Optimizing the Prediction of Bagging and Boosting
نویسندگان
چکیده
منابع مشابه
Bagging, Boosting, and C4.5
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classiier learning systems. Both form a set of classiiers that are combined by voting, bagging by generating replicated boot-strap samples of the data, and boosting by adjusting the weights of training instances. This paper reports results of applying both techniques to a system that le...
متن کاملCombining Bagging and Boosting
Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, i...
متن کاملParallelizing Boosting and Bagging
Bagging and boosting are two general techniques for building predictors based on small samples from a dataset. We show that boosting can be parallelized, and then present performance results for parallelized bagging and boosting using OC1 decision trees and two standard datasets. The main results are that sample sizes limit achievable accuracy, regardless of computational time spent; that paral...
متن کاملBagging Boosting and C
Breiman s bagging and Freund and Schapire s boosting are recent methods for improving the predictive power of classi er learning systems Both form a set of classi ers that are combined by voting bagging by generating replicated boot strap samples of the data and boosting by ad justing the weights of training instances This paper reports results of applying both techniques to a system that learn...
متن کاملMultiple Boosting: a Combination of Boosting and Bagging
Classiier committee learning approaches have demonstrated great success in increasing the prediction accuracy of classiier learning , which is a key technique for datamining. These approaches generate several classiiers to form a committee by repeated application of a single base learning algorithm. The committee members vote to decide the nal classiication. It has been shown that Boosting and ...
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ژورنال
عنوان ژورنال: Indian Journal of Science and Technology
سال: 2015
ISSN: 0974-5645,0974-6846
DOI: 10.17485/ijst/2015/v8i35/78449