COMBINING EXPLORATORY PROJECTION PURSUIT AND PROJECTION PURSUIT REGRESSION WITH APPLICATION TO NEURAL NETWORKS

被引：18

作者：

INTRATOR, N ^{[1
]}

机构：

[1] BROWN UNIV,INST BRAIN & NEURAL SYST,PROVIDENCE,RI 02912

来源：

NEURAL COMPUTATION | 1993年 / 5卷 / 03期

关键词：

D O I：

10.1162/neco.1993.5.3.443

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yield a new family of cost/complexity penalty terms. Some improved generalization properties are demonstrated on real-world problems.

引用

页码：443 / 455

页数：13

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