Ensemble Approaches for Regression: A Survey

• Tipo: Artigo em Revista Científica Internacional
• Data: 2012

Autores

João Mendes-Moreira (Autor) FEUP; Carlos Soares (Autor) FEP; Alípio Mário Jorge (Autor) FCUP; Jorge Freire de Sousa (Autor) FEUP

Revista

Título: ACM Computing Surveys

Vol. 45

Páginas: 1-10

ISSN: 0360-0300

Editora: ACM

Indexação

ISI Web of Knowledge - 425 Citações

ISI Web of Science

Scopus - 524 Citações

Classificação Científica

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia de computadores

Outras Informações

ID Authenticus: P-002-3KA

DOI: 10.1145/2379776.2379786

Abstract (EN): The goal of ensemble regression is to combine several models in order to improve the prediction accuracy in learning problems with a numerical target variable. The process of ensemble learning can be divided into three phases: the generation phase, the pruning phase, and the integration phase. We discuss different approaches to each of these phases that are able to deal with the regression problem, categorizing them in terms of their relevant characteristics and linking them to contributions from different fields. Furthermore, this work makes it possible to identify interesting areas for future research.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 40