Salahudin Mohamed Ibrahim

Do Sophisticated Forecasting Models Beat Naive Baselines? A Reproducible Benchmark with Statistical Significance Testing

Time-series forecasting is a foundational task in data science, yet reported improvements over naive baselines are frequently small, dataset-dependent, and rarely subjected to formal significance testing. We present a reproducible benchmark comparing three families of forecasting...

Explainable and Robust Machine Learning for Phishing URL Detection: A Cross-Dataset Evaluation

Phishing URL detection using machine learning has achieved near-perfect accuracy on popular benchmark datasets, but the extent to which these results generalize across datasets remains unclear. We train a Random Forest classifier on the PhiUSIIL phishing URL dataset (235,795 reco...