Two-Group Classification Using the Bayesian Data Reduction Algorithm

被引:2
|
作者
Kline, Douglas M. [1 ]
机构
[1] Univ N Carolina, Wilmington, NC 28403 USA
关键词
classification; data reduction; neural networks; pattern recognition; CONFIDENCE-INTERVALS; PROBABILITY;
D O I
10.1002/cplx.20284
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The Bayesian data reduction. algorithm (BDRA) is compared to traditional classification methods as well as feed forward artificial neural networks through a rigorous experiment. The BDRA performs comparably to alternative techniques and approaches theoretical optimal classification rates. Furthermore, it has a fundamentally different method for determining class membership. This study is novel in that it explores how the BDRA relates to established techniques, how it might be used in an explanatory manner and how best to use it. (C) 2009 Wiley Periodicals, Inc. Complexity 15: 43-49, 2010
引用
收藏
页码:43 / 49
页数:7
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