With the hype around machine learning (ML) and the rush to transform businesses with it, unsurprisingly, not all ML projects ...

Researchers developed a machine learning model using CatBoost to predict disturbances in drone formations with an R² of 83.3%, significantly improving from the previous baseline of 54%.

Data further showed that a machine learning model outperformed other metrics in terms of diagnostic accuracy (75%) compared with MMSE (55%), clinician analysis (49.5%) and modified TICS (45%).

Georgia Southern University researchers develop a machine learning model with 97.97% accuracy in earthquake forecasting. STATESBORO, GA, UNITED STATES, October 29, 2024 /EINPresswire.com ...

More information: Nina Horat et al, Improving Model Chain Approaches for Probabilistic Solar Energy Forecasting through Post-processing and Machine Learning, Advances in Atmospheric Sciences (2024 ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, molecules, and materials.

A machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous recognized categorization methods.