Data/hora: 12/06/2024 09:34:45

Biblioteca(s): | Embrapa Cerrados.
Data corrente: | 16/06/2000
Data da última atualização: | 16/06/2000
Autoria: | PRADO, H. A.; FRIGERI, S. R.; MACHADO, K. F.; ENGEL, P. M.
Título: | Data mining using combinatorial neural model.
Ano de publicação: | 1999
Fonte/Imprenta: | Revista Tecnologia da Informacao, Brasilia, v.1, n.1, p.16-21, ago.1999.
Idioma: | Inglês
Conteúdo: | This paper addresses two important problems in data mining: scaling machine learning algorithms to very large data bases and the creation of features to make easier the application of these algorithms. The target algorithm is the Combinatorial Neural Model (CNM) ([MAC 89] and [MAC 91]). First we show a description of CNM and then an alternative to generate the CNM netwok. Another important issue is faced: the prunning of the model after the training phase. In the original proposal this prunning is done on the basis of accumulators values on the model. This criteria does not give a precise notion of the accuracy thet results after the prunning. We present an implementation of the model with a feature based on the wrapper method to prune the network by using the accuracy level instead of the value of accumulators. Finally, we discuss the contributions and future work.
Palavras-Chave: | Information processing.
Thesagro: | Processamento da Informação.
Categoria do assunto: | --
Registro original: | Embrapa Cerrados (CPAC)
Exemplares: | CPAC - (3268-1) - UPC - SP - -- - CRI5231 -  - CRI5231 - DIS