Ensemble Approaches for Regression: A Survey

• Type: Article in International Scientific Journal
• Date: 2012

Authors

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

Journal

Title: ACM Computing Surveys

Vol. 45

Pages: 1-10

ISSN: 0360-0300

Publisher: ACM

Indexing

ISI Web of Knowledge - 435 Citations

ISI Web of Science

Scopus - 536 Citations

Scientific classification

CORDIS: Technological sciences > Engineering > Computer engineering

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 40