基于Scikit-Learn的垃圾短信过滤方法实证研究
wf(2016)
Abstract
文章为有效应对垃圾短信,在短信数据集“SMS Spam Collection”上,以Scikit-Learn为工具,通过实验对比验证,结果表明,在比较的7种垃圾短信过滤统计学习方法中,朴素贝叶斯和支持向量机方法在判别准确率方面明显优于其他方法,这2种方法可以作为其他方法用以比较的基准测试方法。
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Key words
spam messages,Scikit-learn,classification,na?ve Bayes,support vector machine
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