Bayesian Filtering for the Rest of Us
By: Joel Martinez on Friday, November 18, 2005
Reader Level: 
Math, I don't know about you guys, but I could not stand it when I was in school. Well, hindsight being 20/20 and all, I have now learned in my old age as a programmer that math plays a big part n modern systems. Specifically, I have recently been digging into the implementation of Bayesian Spam Filters, a statistical method of determining whether an incoming email is spam or not. To be more specific, here's what Wikipedia has to say about Bayesian Spam Filters:
Bayesian email filters take advantage of Bayes' theorem. Bayes' theorem, in the context of spam, says that the probability that an email is spam, given that it has certain words in it, is equal to the probability of finding those certain words in spam email, times the probability that any email is spam, divided by the probability of finding those words in any email
The interesting thing about this method of classification is that it learns over time. The more you train it in how to differentiate spam from "ham", the better it gets at doing its job. The very idea that an application can take a look at an arbitrary piece of data like an email, and know what to do with it intrigues me.
By writing applications that learn over time and make decisions based on context, the art of application development is taken to the proverbial next level. The purpose of this article is to abstract the messy details of the implementation and give you cold hard code that you can implement in your own projects.
Code is presented in C#
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