Spam SMS (or) Email Detection and Classification using Machine Learning

Abstract

Spam is an unwanted message or SMS sent on mobile phones whose content may be malicious. Scammers send fake text messages to trick people into responding to their SMS and they may hack personal information, password, account number, etc. To avoid being tricked by scammers, proposed a model based on Machine learning Algorithms. The proposed model is implemented using the Naïve Bayes algorithm and term frequency-inverse document frequency vectorizer. Obtained the dataset from Kaggle and trained the model using it. This model consists of a local host website which is obtained through PyCharm IDE. Obtained results show that the model accuracy of 95% and a precision of 100%.

Topics & Concepts