The codes above help to classify a given mail as a spam or non spam.
Directions of use:
- Download the enron1 dataset from http://www2.aueb.gr/users/ion/data/enron-spam/ and copy all the emails from ham and spam folder into a folder named "emails" which should be presented at the same place where these codes are downloaded.
- First run the code extracting_unique_words_from_all_emails.py which helps to make file wordslist.csv which contains the unique words found in emails which occur more than or equal to 100 times in all emails.
- Next run processing_emails_to_find_occurance_of_words.py to find the occurance of each word in the emails dataset and make frequency.csv file which stores the frequency of each important word present in wordlist.csv in every email.
- Finally run the svm_implementation.py code to study the predicted results of Support Vector Machine Algorithm on the dataset.