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It uses machine learning models (Multinomial NB & SVM) to predict whether the email is spam or ligitimate on two corpus namely Ling-spam corpus and Euron-spam corpus.

Home Page: https://appliedmachinelearning.wordpress.com/2017/01/23/email-spam-filter-python-scikit-learn/

Python 100.00%

mail-spam-filtering's Issues

Add run statements in README

It would be helpful to have the procedure on how to run the program after installing the dependencies added to readme.

Sieve filter adaptation

#this I made myself. This sieve script blocks entire domains from sending emails.
require "reject";
require "fileinto";
if address :domain ["from","to"]["email.allrecipes.com","surveymonkeyuser.com","arvixe.com","mail.foodandwine.com","blazinggrace.org","treehugger.com","survivalsullivan.com","mail.directactioneverywhere.com","newsletter.popularmechanics.com","comm.capella.edu","googlemail.com","parents.com","howtogeek.com","indwes.edu","e.kotaku.com","emails.parents.com","eml.proflowers.com","heyitsfree.net","peta.org","uta.edu.ec"]
{
discard;}
#this section is used to blacklist specific addresses to avoid blocking legit emails.
if address :all "from" ["[email protected]","[email protected]","[email protected]","[email protected]"]
{reject "this address is blacklisted due to excess emails/spam.";}
#using pm.me for a spamtrap address.
if address :all "to" "[email protected]"
{fileinto"trash";}

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