A new geometric filtering framework for selecting LLM-generated training samples improves few-shot text classification by +2.61 percentage points over SMOTE across 13 datasets, 5 classifiers, 10 augme…
An open-source network intrusion detection system called ML-IDS, built with CatBoost and restricted to Layer 3 and Layer 4 behavioral features, solves the zero-detection problem caused by class imbala…
An arXiv preprint (arXiv:2606.03995) reports an explainable machine learning model that achieved near-perfect three-class classification of Alzheimer's disease, mild cognitive impairment, and normal c…
Researchers developed an XGBoost machine learning model using eight routine clinical features from the Alzheimer's Disease Neuroimaging Initiative dataset that achieved 94.3% accuracy and a 0.982 macr…