SpamBayes is an open source anti-spam software application that uses machine learning to identify and filter out spam emails. It is based on the work of Paul Graham and his team at the University of California, Berkeley. SpamBayes uses a statistical algorithm called a "naive Bayes" classifier to determine whether an email is spam or not. It works by analyzing the words in an email and assigning each word a probability score to determine the likelihood that the email is spam. The more words in the email that have high scores, the more likely it is to be spam. SpamBayes can be used in both desktop and web-based applications and can be integrated with email clients such as Microsoft Outlook and Mozilla Thunderbird.
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