The study is focused on identity theft and cybersecurity in United States. Hence, the study is
aimed at examining the impact of cybersecurity on identity theft in United States using a time …

This paper focuses on ozone prediction in the atmosphere using a machine learning
approach. We utilize air pollutant and meteorological variable datasets from the El Paso …

This paper addresses the pressing issue of diabetes, which is a widespread condition
affecting a huge population worldwide. As cells become less responsive to insulin or fail to …

Road accidents have significant economic and societal costs, with a small number of severe
accidents accounting for a large portion of these costs. Predicting accident severity can help …

Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels.
It may affect various organs and tissues, and even lead to life-threatening complications …

This paper delves into the critical evaluation of four machine learning algorithms: Random
Forest Classifier, Support Vector Machine (SVM), Decision Trees, and KModes. These …

When developing predictive models over a dataset, the model is globally optimized across
the entire feature space to learn a decision boundary. However, when unobservable …

Road accidents have significant economic and societal costs, with a small number of severe
accidents accounting for a large portion of these costs. Predicting accident severity can help …