A Naive Bayes Classifier Demo from Scratch
https://plg.uwaterloo.ca/cgi-bin/cgiwrap/gvcormac/foo06
来自uwateloo收集的邮件数据，本代码采用中文邮件版本(trec06c),里面包含了60000多条中文邮件数据，在index里面已经标注好了那些是SPAM(垃圾邮件)或者HAM(正常邮件)。
下载数据集到项目目录，运行PreData(SPAM).py得到预处理好的data目录。将要预测的文本放到text变量中，再运行train.py预测结果。
第一部分词耗时较长，我把第一部预处理好的文件已经放在data/下，可以直接进行第二步。
用下面的语料进行测试，text1被判断成正常邮件，text2为垃圾邮件，符合事实。
text1 = "我是一个外国的留学生\
我很喜欢**的传统艺术\
我想跟您学习毛笔字"
text2 = "您好！我深圳宏易实业有限公司。\
公司在全国各地大城市设有分公司，因进项较多完成不了每月销售额度,\
现我公司有多余的发票可以低点向贵公司代开，供贵公司财务做帐及抵扣,可以验证后付款。"
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