Skip to main content
Article thumbnail
Location of Repository

Diversity-Based Boosting Algorithm

By Jafar A. Alzubi


Boosting is a well known and efficient technique for constructing a classifier ensemble. An ensemble is built incrementally by altering the distribution of training data set and forcing learners to focus on misclassification errors. In this paper, an improvement to Boosting algorithm called DivBoosting algorithm is proposed and studied. Experiments on several data sets are conducted on both Boosting and DivBoosting. The experimental results show that DivBoosting is a promising method for ensemble pruning. We believe that it has many advantages over traditional boosting method because its mechanism is not solely based on selecting the most accurate base classifiers but also based on selecting the most diverse set of classifiers

Topics: Artificial Intelligence, Classification, Boosting, Di-versity, Game Theory, Electronic computers. Computer science, QA75.5-76.95, Instruments and machines, QA71-90, Mathematics, QA1-939, Science, Q
Publisher: The Science and Information (SAI) Organization
Year: 2016
OAI identifier:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.