Textual, Non-Textual, and Hybrid Feature Engineering for SMS Spam Classification

Contemporary spam filters increasingly rely on resource-intensive, deep learning models. This study evaluates the performance, robustness, and deployability of lightweight learning models. It provides a head-to-head evaluation of probabilistic (Naïve Bayes) and margin-based (Support Vecto...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Aditi Ranjit Kumar Verma, Shriya Sadana
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	BoW BNB feature selection hybrid feature engineering SMS spam classification structured metadata features
Online Access:	https://ieeexplore.ieee.org/document/11202451/