Spam Email Detection Using TF-IDF Based Support Vector Machine Approach

Kasturi, K and Kalpana, Y. Spam Email Detection Using TF-IDF Based Support Vector Machine Approach. Spam Email Detection Using TF-IDF Based Support Vector Machine Approach, 6 (20). pp. 718-725. ISSN 2581-9429

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Abstract

Nowadays, all the people are communicating official information through emails. Spam mail
is the major issue on the internet. It is easy to send an email which contains spam messages by the
spammers. Spam fills our inbox with several irrelevant emails. Spammers can steal sensitive information
from our device like files, contact. Even though we have the latest technology, it is challenging to detect
spam emails. This paper aims to propose a Term Frequency Inverse Document Frequency (TFIDF)
approach by implementing the Support Vector Machine algorithm. The results are compared in terms of
the confusion matrix and accuracy. and precision. This approach gives an accuracy of 99.9% on training
data and 98.2% on testing data achieved by using the Term Frequency Inverse Document Frequency
(TFIDF) based Support Vector Machine (SVM) system.

Item Type: Article
Subjects: Computer Science Engineering > Machine Learning
Domains: Computer Science Engineering
Depositing User: Mr IR Admin
Last Modified: 15 May 2026 11:18
URI: https://ir.vistas.ac.in/id/eprint/19696

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