AdaCost: Misclassification Cost-Sensitive Boosting

Each type of classifier has its own advantages as well as certain shortcomings. In this paper, we take the advantages of the associative classifier and the Naive Bayes Classifier to make up the shortcomings of each other, thus improving the accuracy of ...

Highlights The performance of AdaBoost algorithms were compared with support vector machine and Bayesian classifiers for pecan defect classification. AdaBoost classifiers took least time and gave best classification accuracy. AdaBoost classifiers ...

For the one-against-one approach, all the binary classifiers that form a one-against-one classifier should be sufficiently competent. If some of the classifiers are not competent, the consequences might be invalid classification results. To address the ...