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Combining clustering and active learning for the detection and learning of new ...

Combining clustering and active learning for the detection and learning of new ...

Made available in DSpace on 2019-10-04T12:38:21Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-09-17; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); Discriminative classification models often assume all classes are available at the training phase. As such models do not have a strategy to learn new concepts from available unlabeled instances, they usually work poorly when unknown classes ...

Evolving Gaussian mixture models with splitting and merging mutation operators

A differential evolution algorithm to optimise the combination of classifier an...

Using metaheuristics to optimize the combination of classifier and cluster ense...

Towards the use of metaheuristics for optimizing the combination of classifier ...

Competitive learning with pairwise constraints