Adnan, Muhammad; Imam, Muhammad Osama; Javed, Muhammad Furqan; Murtza, Iqbal (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-20)
Spam emails pose a substantial cybersecurity danger, necessitating accurate classification to reduce unwanted messages and
mitigate risks. This study focuses on enhancing spam email classification accuracy using stacking ensemble machine learning
techniques.We trained and tested five classifiers: logistic regression, decision tree, K-nearest neighbors (KNN), Gaussian naive
Bayes and AdaBoost. To ...