Author

Andre Sebastian Samaniego Buñay

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Open access Sep 2026

Comparative Analysis of Transformer-Based and ClassicalMachine Learning Models for Phishing Email Detection:A Multi-Source Dataset Evaluation with Explainability

This paper compares five classifiers: Multinomial Naive Bayes, Random Forest, Bidirectional Long Short-Term Memory, BiLSTM, DistilBERT, and BERT-base, and finds that BERT-base achieves the highest F1-score and DistilBERT the lowest, representing the strongest accuracy–latency trade-off in the evaluated environment.

Andre Sebastian Samaniego Buñay, Ariel Misael Orellana Albarracin, Joel Marcelo Chuquimarca Pomagualli · Enfoque UTE · 0 citations