Previous methods struggle to incorporate real-time data or account for nonlinear interactions among macroeconomic variables.

Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania.

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Scientists are using machine learning to find new treatments among thousands of old medicines. Joseph Coates, left, owes his life to an A.I. model developed by Dr. David Fajgenbaum and the rest of ...

Types of Machine Learning: Supervised Learning: Involves training a model on labeled data. Regression: Predicting continuous numerical values (e.g., housing prices, stock prices). Classification: ...

The study employs a Bayesian Optimization-enhanced Random Forest (BO_RF) algorithm for binary classification and a hybrid Logistic Regression and Random Forest (LR_RF) algorithm for multiclass ...