文件名称:Bayesian
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Windows] [Visual.Net] [源码]
- 上传时间：
- 2013-06-29
- 文件大小：
- 2.58mb
- 下载次数：
- 0次
- 提 供 者：
- L**
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
贝叶斯分类器的基本实现，数据可以自行添加，中英文皆可-Bayesian classifier basic implementation, the data can add, in English or
(系统自动生成,下载前可以参看下载内容)
下载文件列表
Bayesian\Bayesian\Bayesian.cpp
........\........\Bayesian.vcxproj
........\........\Bayesian.vcxproj.filters
........\........\Bayesian.vcxproj.user
........\........\Debug\Bayesian.exe.embed.manifest
........\........\.....\Bayesian.exe.embed.manifest.res
........\........\.....\Bayesian.exe.intermediate.manifest
........\........\.....\Bayesian.lastbuildstate
........\........\.....\Bayesian.log
........\........\.....\Bayesian.obj
........\........\.....\Bayesian.pch
........\........\.....\Bayesian_manifest.rc
........\........\.....\CL.read.1.tlog
........\........\.....\CL.write.1.tlog
........\........\.....\link-cvtres.read.1.tlog
........\........\.....\link-cvtres.write.1.tlog
........\........\.....\link.10096-cvtres.read.1.tlog
........\........\.....\link.10096-cvtres.write.1.tlog
........\........\.....\link.10096.read.1.tlog
........\........\.....\link.10096.write.1.tlog
........\........\.....\link.read.1.tlog
........\........\.....\link.write.1.tlog
........\........\.....\mt.read.1.tlog
........\........\.....\mt.write.1.tlog
........\........\.....\rc.read.1.tlog
........\........\.....\rc.write.1.tlog
........\........\.....\stdafx.obj
........\........\.....\vc100.idb
........\........\.....\vc100.pdb
........\........\ReadMe.txt
........\........\result.txt
........\........\source.txt
........\........\stdafx.cpp
........\........\stdafx.h
........\........\targetver.h
........\Bayesian.sdf
........\Bayesian.sln
........\Bayesian.suo
........\Debug\Bayesian.exe
........\.....\Bayesian.ilk
........\.....\Bayesian.pdb
........\ipch\bayesian-1e294ba8\bayesian-5b54f938.ipch
........\Bayesian\Debug
........\ipch\bayesian-1e294ba8
........\Bayesian
........\Debug
........\ipch
Bayesian