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For instance, the word "Nigeria" appears often in spam, so you could use a spam filter which identifies anything with that word in it as spam. But what if your business involves writing a guidebook on Nigerian Wildlife Conservation? Clearly a more flexible approach is necessary. Additionally spammers will adapt their content over time and will no longer use the word "Nigeria" or the words "Lose Weight Fast", or any number of other common lines. Ideally the software will be able to adapt as the spam changes.

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So, that is what SpamBayes does. It compares the spam and the ham and calculates probabilities. For instance, for me, the word "weight" almost never occurs in legitimate email, but it occurs all the time in 'lose weight fast' spam.

SpamBayes can then look at incoming email, extract the most significant clues and combine the probabilities to produce an overall rating of "spamminess". It flags the messages so that your mailer can handle the different message types.

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You might set it up so that ham goes straight through untouched, spam goes to a folder that you ignore or delete without checking and the unsure messages go to another folder which you can review for errors. There are a number of similar projects to SpamBayes - most are just using the original Paul Graham algorithm.

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Examining the Graham technique with careful testing showed that it did a remarkably good job, but there was considerable room for improvement. See the background page for more.


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The SpamBayes team tinkered with new algorithms, tweaking existing algorithms, and, most importantly, did enormous test runs, slamming tens of thousands of messages against each other, in an attempt to quantify whether or not a change to the system was beneficial. The new algorithm is a combination of work from Gary Robinson and Tim Peters, and provides not just a 'spam' and 'ham' rating, but also an 'unsure' rating, for those messages where it can't work out how to rate the message.

The code implemented in Python is currently available from a variety of methods from the downloads page. There are now a couple of end-user applications available for those excited by the bleeding edge - these are detailed on the Applications page, and available as part of the source download. Most of the heavy lifting on this project was done by Tim Peters, with the cast of spambayes obsessive-compulsives providing ideas, heckling, and testing. This process will work on your iPhone, iPod Touch or iPad. While the screen shots are from an iPhone running iOS, the same settings should work on any iOS device.

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To get the correct settings for your email account, log in to your Bluehost hosting account and open the Email Manager. From the Email Manager , click on the email configuration tab to see all possible settings. Apply these settings in the steps below. User Name: Your email address.

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Password: The password for your email address. Outgoing Mail Server Although iOS may indicate these fields as optional, please enter your full email address and password Host Name: This is the same as the incoming server. You can even hide your friends from the screen so the spam is easy to recognize.

This clever type of spam filtering learns which of your email is spam and which is not very quickly and accurately. If you accidentally delete an email, you can restore it back to your email account Pro version only. Check mail at different intervals. Play a sound when an email arrives, or be notified visually. Email log. Comprehensive help documentation on this site. This program is so simple to use, just leave it going and process your mail when you want to.

There is no spy-ware contained in this program, we do not monitor your actions or email.

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When you register this program, we will not give your email address or personal details to anyone. Using MailWasher is easy!

PREVIEW Easily preview the messages in your email account to see what the sender has to say before downloading your email to your computer. Pretty impressive if you ask us!