Symbolic approach to classify large data sets

被引：0

作者：

de Carvalho, FDT ^{[1
]}

Anselmo, CAD ^{[1
]}

de Souza, RMCR ^{[1
]}

机构：

[1] Univ Fed Pernambuco, CIN, Ctr Informat, BR-50740540 Recife, PE, Brazil

来源：

DATA ANALYSIS, CLASSIFICATION, AND RELATED METHODS | 2000年

关键词：

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The aim of this work is to present an approach to classify large data sets based on a Boolean symbolic classifier as described in Yaguchi et al (1996) and Ichino et al (1996). Compared with this last classifier, our system keeps the concept of mutual neighbours between examples (Ichino et al 1996) but introduces some modifications in both learning step (generalisation tools) and allocation step (matching functions). As an example of large data set processing, a particular kind of simulated images will be classified according to this approach.

引用

页码：375 / 380

页数：6

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