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贝叶斯分类器的应用-论文下载
论文:
摘 要:贝叶斯决策理论是统计模式识别中的一个基本方法。依据贝叶斯决策理论设计的分类器具有最优
的性能, 即所实现的分类错误率或风险在所有可能的分类器中是最小的, 因此经常被用来衡量其他分类器设
计方法的优劣。贝叶斯决策是一个很有效的分类工具, 但它仍然存在着一定的错误率和风险, 因此还需进一
步的改善和完善。
关键词: 贝叶斯决策理伦; 最优; 分类错误率; 分类工具
中图分类号: 1 ' P 3 9 1 . 4 文献标识码: A 文章编号: 1 6 7 1— 6 5 5 8 ( 2 0 0 8 ) 0 2— 0 7一 o 4
2009-10-23
Statistical Pattern Recognition-2nd edition
This book provides an introduction to statistical pattern recognition theory and techniques.
Most of the material presented is concerned with discrimination and classification and
has been drawn from a wide range of literature including that of engineering, statistics,
computer science and the social sciences. The book is an attempt to provide a concise
volume containing descriptions of many of the most useful of today’s pattern process-
ing techniques, including many of the recent advances in nonparametric approaches to
discrimination developed in the statistics literature and elsewhere. The techniques are
illustrated with examples of real-world applications studies. Pointers are also provided
to the diverse literature base where further details on applications, comparative studies
and theoretical developments may be obtained.
2009-09-26
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