这两天做了一个hadoop上跑的分类算法——贝叶斯分类。下面介绍一下实验的运行过程。。
1,获取数据集:http://people.csail.mit.edu/jrennie/20Newsgroups/20news-bydate.tar.gz(做分类实验通常用的数据集)
2,解压数据:我的位置:/home/XXXXXX/hadoop/mahout/mahout-distribution-0.6/examples/bin/work
3,预处理训练数据集并需要把txtfile转换成sequenceFile(mahout处理的文件必须是sequenceFile格式的)。命令:mahout org.apache.mahout.classifier.bayes.PrepareTwentyNewsgroups -p /home/XXXXXX/hadoop/mahout/mahout-distribution-0.6/examples/bin/work/20news-bydate-train -o /home/XXXXXX/hadoop/mahout/mahout-distribution-0.6/examples/bin/work/bayes-train-input -a org.apache.mahout.vectorizer.DefaultAnalyzer -c UTF-8
4,将work下的bayes-train-input放到hadoop的分布式文件系统上的 20news-input。命令:hadoop dfs -put /home/XXXXXX/hadoop/mahout/mahout-distribution-0.6/examples/bin/work/bayes-train-input 20news-input
5,用处理好的训练数据集进行训练得出分类模型即中间结果。命令:mahout trainclassifier -i 20news-input -o newsmodel -type bayes -ng 3 -source hdfs
查看分类模型的内容:命令:hadoop fs -lsr /user/hadoop/newsmodel;还可以导出到本地的txt格式查看:命令:mahout seqdumper -s /user/XXXXXX/newsmodel/trainer-tfIdf//trainer-tfIdf/part-00000 -o /home/XXXXXX/hadoop/out/part-1
插入一张图片,不然显得太单调了:
6,用模型测试。命令:mahout testclassifier -m newsmodel -d 20news-input -type bayes -ng 3 -source hdfs -method mapreduce
用模型测试时还有点小错误,先这样写上,等测试成功了然后再纠正此处的错误。。见谅
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