Busca avançada
Ano de início
Entree


A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels

Texto completo
Autor(es):
da Silva, Tiago Pinho ; Alves Souza, Vinicius Mourio ; Almeida Prado Alves Batista, Gustavo Enrique ; Camargo, Heloisa de Arruda
Número total de Autores: 4
Tipo de documento: Artigo Científico
Fonte: PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2018; v. 11401, p. 9-pg., 2019-01-01.
Resumo

In data stream learning, classification is a prominent task which aims to predict the class labels of incoming examples. However, in classification, most of the approaches from literature make assumptions that limit the usefulness of the methods in real scenarios such as the supposition that the label of an example will be available right after its prediction, i.e., there is no time delay to acquiring actual labels. It is a very optimistic assumption, since labeling the entire data stream is usually not feasible. Some recent approaches overcome this limitation, considering unsupervised learning methods to deal with delayed labels. Also, some proposals explore concepts of fuzzy set theory to add more flexibility to the learning process, although restricted to data streams with no delayed labels. In this paper, we propose a fuzzy classifier for data streams with infinitely delayed labels called FuzzMiC. Our algorithm generates a model based on fuzzy micro-clusters that provides flexible class boundaries and allows the classification of evolving data streams. Experiments show that our approach is promising in dealing with incremental changes. (AU)

Processo FAPESP: 16/04986-6 - Armadilhas e sensores inteligentes: uma abordagem inovadora para controle de insetos peste e vetores de doenças
Beneficiário:Gustavo Enrique de Almeida Prado Alves Batista
Modalidade de apoio: Auxílio à Pesquisa - Programa eScience e Data Science - Regular
Processo FAPESP: 18/05859-3 - Armadilhas e sensores inteligentes: uma abordagem inovadora para controle de insetos peste e vetores de doenças
Beneficiário:Vinícius Mourão Alves de Souza
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado