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...

وصف كامل

التفاصيل البيبلوغرافية

الحاوية / القاعدة:	IEEE Access
المؤلفون الرئيسيون:	Aditi Ranjit Kumar Verma, Shriya Sadana
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	IEEE 2025-01-01
الموضوعات:	BoW BNB feature selection hybrid feature engineering SMS spam classification structured metadata features
الوصول للمادة أونلاين:	https://ieeexplore.ieee.org/document/11202451/