Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks

被引:0
作者
Nicoletti, Maria do Carmo [1 ]
Bertini, Joao R., Jr. [2 ]
Elizondo, David [3 ]
Franco, Leonardo [4 ]
Jerez, Jose M. [4 ]
机构
[1] Univ Fed Sao Carlos, CS Dept, Sao Carlos, SP, Brazil
[2] Univ Sao Paulo, ICMA, Sao Carlos, SP, Brazil
[3] De Montfort Univ, Leicester, Leics, England
[4] Univ Malaga, Malaga, Spain
来源
CONSTRUCTIVE NEURAL NETWORKS | 2009年 / 258卷
基金
巴西圣保罗研究基金会;
关键词
LIMITATIONS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This chapter presents and discusses several well-known constructive neural network algorithms suitable for constructing feedforward architectures aiming at classification tasks involving two classes. The algorithms are divided into two different groups: the ones directed by the minimization of classification errors and those based on a sequential model. In spite of the focus being on two-class classification algorithms, the chapter also briefly comments on the multiclass versions of several two-class algorithms, highlights some of the most popular constructive algorithms for regression problems and refers to several other alternative algorithms.
引用
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页码:1 / +
页数:7
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