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Multiclass Boosting with Adaptive Group-BasedkNN and Its Application in Text Categorization
2012
Mathematical Problems in Engineering
AdaBoost is an excellent committee-based tool for classification. However, its effectiveness and efficiency in multiclass categorization face the challenges from methods based on support vector machine (SVM), neural networks (NN), naïve Bayes, andk-nearest neighbor (kNN). This paper uses a novel multi-class AdaBoost algorithm to avoid reducing the multi-class classification problem to multiple two-class classification problems. This novel method is more effective. In addition, it keeps the
doi:10.1155/2012/793490
fatcat:uyzxteeey5gd7nubhxady5zspq