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An Imbalance-Aware and Structure-Enriched Framework for SMS Spam Detection Using Ensemble Learning

This paper proposes a novel hybrid framework for SMS spam detection that integrates multi-criteria decision making for feature selection, SMOTE for addressing class imbalance, and a Stacking-based ensemble classifier to achieve superior performance in precision, F1-score, and AUC on benchmark datasets.

Original authors: Mahdi Sarbazi, Mohammad Fathi, Keyhan Khamforoosh

Published 2026-09-22
📖 1 min read☕ Coffee break read

Original authors: Mahdi Sarbazi, Mohammad Fathi, Keyhan Khamforoosh

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

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