Adapting peepholing to regression trees

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2005

Autores

Torgo, L (Autor) FEP; Marques, J (Autor) Outra

Ata de Conferência Internacional

Título: Progress in Artificial Intelligence, 12th Portuguese Conference on Artificial Intelligence, EPIA 2005

Páginas: 293-303

12th Portuguese Conference on Artificial Intelligence

Covilhã, Portugal, December 5-8

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Classificação Científica

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

Outras Informações

ID Authenticus: P-000-6MN

DOI: 10.1007/11595014_30

Abstract (EN): This paper presents an adaptation of the peepholing method to regression trees. Peepholing was described as a means to overcome the major computational bottleneck of growing classification trees by Catlett [3]. This method involves two major steps: shortlisting and blinkering. The former has the goal of eliminating some continuous variables from consideration when growing the tree, while the second tries to restrict the range of values of the remaining continuous variables that should be considered when searching for the best cut point split. Both are effective means of overcoming the most costly step of growing tree-based models: sorting the values of the continuous variables before selecting their best split. In this work we describe the adaptations that are necessary to use this method within regression trees. The major adaptations involve developing means to obtain biased estimates of the criterion used to select the best split of these models. We present some preliminary experiments that show the effectiveness of our proposal.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11