Skip to content

The model with accuracy score 0.98 learns the email and creates a 'bag of words', from which the probability of an email to be spam with the presence of that word is calculated. Test emails are checked and if those threat words are found it is labeled as spam.

Notifications You must be signed in to change notification settings

Manjari-99/email_spam_verifier_99

Repository files navigation

email_spam_verifier

An essential implementation of sentiment analysis through machine learning concepts. The model learns the email and creates a 'bag of words', from which the probability of an email to be spam with the presence of that word is calculated. Test emails are checked and if those threat words are found it is labeled as spam. A preliminary website has also been created where users can paste their emails to check whether it is spam or not.

About

The model with accuracy score 0.98 learns the email and creates a 'bag of words', from which the probability of an email to be spam with the presence of that word is calculated. Test emails are checked and if those threat words are found it is labeled as spam.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published