A Hybrid AIS-SVM Ensemble Approach for Text Classification

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2011

Autores

Mario Antunes (Autor) Outra; Catarina Silva (Autor) Outra; Bernardete Ribeiro (Autor) Outra; Manuel Correia (Autor) FCUP

Ata de Conferência Internacional

Título: ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, PT II

Páginas: 342-352

10th International Conference on Artificial Neural Networks and Genetic Algorithms

Ljubljana, SLOVENIA, APR 14-16, 2011

Indexação

ISI Web of Knowledge - 6 Citações

Scopus - 9 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-002-XXR

DOI: 10.1007/978-3-642-20267-4_36

Abstract (EN): In this paper we propose and analyse methods for expanding state-of-the-art performance on text classification. We put forward an ensemble-based structure that includes Support Vector Machines (SVM) and Artificial Immune Systems (AIS). The underpinning idea is that SVM-like approaches can be enhanced with A IS approaches which can capture dynamics in models. While having radically different genesis, and probably because of that, SVM and AIS can cooperate in a committee setting, using a heterogeneous ensemble to improve overall performance, including a confidence on each system classification as the differentiating factor. Results on the well-known Reuters-21578 benchmark are presented, showing promising classification performance gains, resulting in a classification that improves upon all baseline contributors of the ensemble committee.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11