Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

With volatility so closely tied to investment risk and returns, it's no wonder that a statistical method that captured time-varying volatility was deemed worthy of a Nobel Prize. Since its creation, ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

An AI model using deep transfer learning—the most advanced form of machine learning—has predicted spoken language outcomes ...

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...