文件名称:ex1
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贝叶斯方法一篇比较科普的中文介绍可以见pongba的平凡而神奇的贝叶斯方法: http://mindhacks.cn/2008/09/21/the-magical-bayesian-method/，实际实现一个贝叶斯分类器之后再回头看这篇文章，感觉就很不一样。
在模式识别的实际应用中，贝叶斯方法绝非就是post正比于prior*likelihood这个公式这么简单，一般而言我们都会用正态分布拟合likelihood来实现。-pattern identification
在模式识别的实际应用中，贝叶斯方法绝非就是post正比于prior*likelihood这个公式这么简单，一般而言我们都会用正态分布拟合likelihood来实现。-pattern identification
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下载文件列表
ex1/
ex1/computeCost.m
ex1/computeCostMulti.m
ex1/ex1.m
ex1/ex1data1.txt
ex1/ex1data2.txt
ex1/ex1_multi.m
ex1/featureNormalize.m
ex1/gradientDescent.m
ex1/gradientDescentMulti.m
ex1/lib/
ex1/lib/jsonlab/
ex1/lib/jsonlab/AUTHORS.txt
ex1/lib/jsonlab/ChangeLog.txt
ex1/lib/jsonlab/jsonopt.m
ex1/lib/jsonlab/LICENSE_BSD.txt
ex1/lib/jsonlab/loadjson.m
ex1/lib/jsonlab/loadubjson.m
ex1/lib/jsonlab/mergestruct.m
ex1/lib/jsonlab/README.txt
ex1/lib/jsonlab/savejson.m
ex1/lib/jsonlab/saveubjson.m
ex1/lib/jsonlab/varargin2struct.m
ex1/lib/makeValidFieldName.m
ex1/lib/submitWithConfiguration.m
ex1/normalEqn.m
ex1/plotData.m
ex1/submit.m
ex1/warmUpExercise.m
ex1/computeCost.m
ex1/computeCostMulti.m
ex1/ex1.m
ex1/ex1data1.txt
ex1/ex1data2.txt
ex1/ex1_multi.m
ex1/featureNormalize.m
ex1/gradientDescent.m
ex1/gradientDescentMulti.m
ex1/lib/
ex1/lib/jsonlab/
ex1/lib/jsonlab/AUTHORS.txt
ex1/lib/jsonlab/ChangeLog.txt
ex1/lib/jsonlab/jsonopt.m
ex1/lib/jsonlab/LICENSE_BSD.txt
ex1/lib/jsonlab/loadjson.m
ex1/lib/jsonlab/loadubjson.m
ex1/lib/jsonlab/mergestruct.m
ex1/lib/jsonlab/README.txt
ex1/lib/jsonlab/savejson.m
ex1/lib/jsonlab/saveubjson.m
ex1/lib/jsonlab/varargin2struct.m
ex1/lib/makeValidFieldName.m
ex1/lib/submitWithConfiguration.m
ex1/normalEqn.m
ex1/plotData.m
ex1/submit.m
ex1/warmUpExercise.m
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