HAL (France)
open access
Machine Learning-Based Email Spam Detection: Accuracy, Overfitting and Robustness Analysis
This study evaluates classic and modern machine-learning methods for email spam detection using term frequency and inverse document frequency (TF-IDF) features and a public dataset of ham and spam emails. Nineteen classifiers were trained and compared with accuracy, precision, recall, F1, and varian
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