prakharjadaun/Feature-Extraction-for-Spam-Email-Detection
Implemented Preprocessing steps, Feature Extraction techniques and Naive Bayes Classifier in C++. Moreover, we have also implemented all the steps using python for comparative analysis.
This helps individuals and organizations filter unwanted bulk emails (spam) from important messages (ham) to improve inbox management. It takes incoming email content as input and classifies each email as either spam or legitimate, presenting a cleaner inbox. Students and working professionals who rely heavily on email for communication will find this useful.
No commits in the last 6 months.
Use this if you need a system to automatically differentiate between spam and important emails, aiming to reduce inbox clutter and prevent phishing attempts.
Not ideal if you require advanced email management features beyond basic spam filtering, such as email archiving, task management, or complex rule-based sorting.
Stars
8
Forks
2
Language
C++
License
MIT
Category
Last pushed
Dec 17, 2022
Commits (30d)
0
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