Enhancing Email Fraud Detection Using SVM: A Comparative Analysis with Other Machine Learning Models

Author(s)	Mr. Sudhir Satish Patil
Country	India
Abstract	The primary objective of this study is to develop a robust spam detection system by leveraging feature extraction and classification techniques. Our approach involves preprocessing email content to remove stopwords, punctuation, and non-informative terms, followed by lemmatization to standardize word forms.
Keywords	Email Fraud Detection, Spam Classification, Support Vector Machine (SVM), Machine Learning Models, Feature Extraction, Text Preprocessing, TF-IDF, Natural Language Processing (NLP), Comparative Analysis, Cybersecurity, Phishing Detection, Spam Filtering, Rough Set Classifier, Supervised Learning, Performance Metrics
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-03
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.40462
Short DOI	https://doi.org/g9dgx3

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International Journal For Multidisciplinary Research