文件名称:spam-classification--matlab
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机器学习中的垃圾邮件分类程序,用matlab做的。从以下链接下载垃圾邮件数据(spam data):(数据已下载,放在spambase.zip)
http://www-stat.stanford.edu/~tibs/ElemStatLearn/index.html
该数据包含57个邮件信息相关的变量,每条邮件可以被分类为垃圾邮件(Y=1)和非垃圾邮件(Y=0)。输出Y的值在文件中每一列的末尾。练习的目标是要预测电子邮件是否为垃圾邮件。
-Machine Learning spam classification procedures, using matlab to do. Data (spam data) from the following link to download the junk mail: (data has been downloaded, put spambase.zip) http://www-stat.stanford.edu/ ~ tibs/ElemStatLearn/index.html The data includes 57 e-mail messages related variables, each message can be classified as spam (Y = 1) and non-spam (Y = 0). Y value of the output end of each column in the file. The goal is to predict exercise email is spam.
http://www-stat.stanford.edu/~tibs/ElemStatLearn/index.html
该数据包含57个邮件信息相关的变量,每条邮件可以被分类为垃圾邮件(Y=1)和非垃圾邮件(Y=0)。输出Y的值在文件中每一列的末尾。练习的目标是要预测电子邮件是否为垃圾邮件。
-Machine Learning spam classification procedures, using matlab to do. Data (spam data) from the following link to download the junk mail: (data has been downloaded, put spambase.zip) http://www-stat.stanford.edu/ ~ tibs/ElemStatLearn/index.html The data includes 57 e-mail messages related variables, each message can be classified as spam (Y = 1) and non-spam (Y = 0). Y value of the output end of each column in the file. The goal is to predict exercise email is spam.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
spambase/LDA.asv
spambase/LDA.m
spambase/naiveBayes.m
spambase/naiveBayes_gaussian.m
spambase/QDA.asv
spambase/QDA.m
spambase/spambase.data
spambase/spambase.DOCUMENTATION
spambase/spambase.names
spambase/spamdetect.m
垃圾邮件分类报告.docx
spambase
spambase/LDA.m
spambase/naiveBayes.m
spambase/naiveBayes_gaussian.m
spambase/QDA.asv
spambase/QDA.m
spambase/spambase.data
spambase/spambase.DOCUMENTATION
spambase/spambase.names
spambase/spamdetect.m
垃圾邮件分类报告.docx
spambase
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