weka文本分类例子调用

weka包里面只包含jre,如果要自己编译java程序调用weka的工具包,必须按照jdk,版本是jdk1.6.0_26.

1.安装jdk,然后配置好环境变量JAVA_HOME,PATH,CLASSPATH

1)JAVA_HOME

C:\Program Files\Java\jdk1.6.0_26

 

2) Path使得系统可以在任何路径下识别java命令，设为：

%JAVA_HOME%/bin;%JAVA_HOME%/jre/bin

3) CLASSPATH为java加载类(class or lib)路径，只有类在classpath中，java命令才能识别，设为：

.;%JAVA_HOME%/lib/dt.jar;%JAVA_HOME%/lib/tools.jar (要加.表示当前路径)

其中注意添加CLASSPATH .;

 

2.运行weka的MessageClassifier例子

三个参数 -m -t -c

-m 要分析的文件

-t 建立的模型

-c 分类的类型 hit/miss

三个参数都有时，是训练；

没有-c时，是预测。

训练

If you run the MessageClassifier for the first time, you need to provide labeled examples to build a classifier from, i.e., messages ("-m") and the corresponding classes ("-c"). Since the data and the model are kept for future use, one has to specify a filename, where the MessageClassifier is serialized to ("-t").

Here's an example, that labels the message email1.txt as miss:

>java MessageClassifier -m email1.txt -c miss -t messageclassifier.model

Repeat this for all the messages you want to have classified.

分类

Classifying an unseen message is quite straight-forward, one just omits the class option ("-c"). The following call

>java MessageClassifier -m email1023.txt -t messageclassifier.model

will produce something like this:

>Message classified as : miss