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

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%.

• Publication year

  2023

• Venue

  2023 5th International Conference on Smart Systems and Inventive Technology (ICSSIT)

• Publication date

  2023-01-23

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICSSIT55814.2023.10060908
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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