Semi Supervised Learning Based In Disagreement
Mostrando 1-2 de 2 artigos, teses e dissertações.
-
1. Abordagens para aprendizado semissupervisionado multirrótulo e hierárquico / Multi-label and hierarchical semi-supervised learning approaches
In machine learning, the task of classification consists on creating computational models that are able to automatically identify the class of objects belonging to a predefined domain from a set of examples whose class is known a priori. There are some classification scenarios in which each object can be associated to more than one class at the same time. Mo
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 25/10/2011
-
2. Semi-supervised learning based in disagreement by similarity / Classificação semi-supervisionada baseada em desacordo por similaridade
Semi-supervised learning is a machine learning paradigm in which the induced hypothesis is improved by taking advantage of unlabeled data. Semi-supervised learning is particularly useful when labeled data is scarce and difficult to obtain. In this context, the Cotraining algorithm was proposed. Cotraining is a widely used semisupervised approach that assumes
Publicado em: 2010