Simulation of the ensemble generation process: The divergence between data and model similarity

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Pinto, F (Autor) Outra; Mendes Moreira, J (Autor) FEUP; Soares, C (Autor) FEUP; Rossetti, RJF (Autor) Outra

Ata de Conferência Internacional

Título: ESM'2014 - The 2014 European Simulation and Modelling Conference, Modelling and Simulation '2014

Páginas: 103-107

ESM'2014 - 28th European Simulation and Modelling Conference, Porto, Portugal, October 22-24, 2014

Indexação

ISI Web of Knowledge

Scopus - 0 Citações

Classificação Científica

CORDIS: Ciências Físicas > Ciência de computadores > Cibernética > Inteligência artificial

Outras Informações

ID Authenticus: P-00A-5D6

Abstract (EN): In this paper we present a Netlogo simulation model for a Data Mining methodological process: ensemble classifier generation. The model allows to study the trade-off between data characteristics and diversity, a key concept in Ensemble Learning. We studied the re¿ search hypothesis that data characteristics should also be taken into account while generating ensemble classifier models. The results of our experiments indicate that diversity is in fact a key concept in Ensemble Learning but regarding our research hypothesis, the findings axe inconclusive.

Idioma: Inglês

Tipo (Avaliação Docente): Científica