Dynamic ensemble selection for multi-class classification with one-class classifiers
In this paper we deal with the problem of addressing multi-class problems with
decomposition strategies. Based on the divide-and-conquer principle, a multi-class problem …
decomposition strategies. Based on the divide-and-conquer principle, a multi-class problem …
Two combination stages of clustered one-class classifiers for writer identification from text fragments
B Hadjadji, Y Chibani - Pattern Recognition, 2018 - Elsevier
Writer identification based on handwritten fragments has been reported to give interesting
performance. However, while the fragmentation process, inconsistent fragments are …
performance. However, while the fragmentation process, inconsistent fragments are …
Ensembles of Deep One-Class Classifiers for Multi-Class Image Classification
A Novotny, G Bebis, A Tavakkoli… - Available at SSRN … - papers.ssrn.com
Traditional methods for multi-class classification (MCC) involve using a monolithic feature
extractor and classifier trained on data from all the classes simultaneously. These methods …
extractor and classifier trained on data from all the classes simultaneously. These methods …
Contribution of using one-class classification combination for multi-class pattern recognition
B Hadjadji - 2017 - ccdz.cerist.dz
Résumé Usual multi-class classifiers take in consideration either the entire classes for
generating the classification model, such as the neural networks. In contrast, the One-Class …
generating the classification model, such as the neural networks. In contrast, the One-Class …