The proliferation of dApps is increasing the attack surface for exploitable vulnerabilities in smart contracts, and thus there is a need for verifiable detection methodologies. The Random Forest ...

Train classification model with default params in silent mode. Calc model predictions on custom data set, output will contain evaluated class1 probability: catboost fit --learn-set train.tsv ...

ABSTRACT: Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and ...

Machine learning models effectively predicted in-hospital mortality among intensive care unit patients with lymphoma, according to research. “Lymphoma is a severe condition with high mortality rates, ...

A FastAPI app for Parkinson’s disease prediction using a pre-trained model. Offers a sleek, animated UI for inputting five voice metrics (spread1, PPE, spread2, MDVP:Fo(Hz), MDVP:Flo(Hz)). Git-ready ...

Abstract: This study employs machine learning classifiers, including Logistic Regression, Random Forest Classifier, Extra Trees Classifier, XGB Classifier, LGBM Classifier, and CatBoost Classifier, to ...

1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...