mahout贝叶斯算法开发思路（拓展篇）一

mahout贝叶斯算法开发思路（拓展篇）1

首先说明一点，此篇blog解决的问题是就下面的数据如何应用mahout中的贝叶斯算法？（这个问题是在上篇（。。。完结篇）blog最后留的问题，如果想直接使用该工具，可以在mahout贝叶斯算法拓展下载）：

usage: <command> [Generic Options] [Job-Specific Options]Generic Options: -archives <paths>              comma separated archives to be unarchived                                on the compute machines. -conf <configuration file>     specify an application configuration file -D <property=value>            use value for given property -files <paths>                 comma separated files to be copied to the                                map reduce cluster -fs <local|namenode:port>      specify a namenode -jt <local|jobtracker:port>    specify a job tracker -libjars <paths>               comma separated jar files to include in                                the classpath. -tokenCacheFile <tokensFile>   name of the file with the tokensJob-Specific Options:                                                             --input (-i) input               Path to job input directory.                   --output (-o) output             The directory pathname for output.             --labelIndex (-li) labelIndex    The path to store the label index in           --help (-h)                      Print out help                                 --tempDir tempDir                Intermediate output directory                  --startPhase startPhase          First phase to run                             --endPhase endPhase              Last phase to run 

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