Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector ...

Six machine learning (ML) algorithms: Linear Regression, Random Forest, Gradient Boosting, XGBoost, LightGBM (Light Gradient Boosting Machine), and Support Vector Regression were used to train models ...

The integration of Machine Learning stands as a prominent solution to unravel the intricacies inherent to scientific data. While diverse machine learning algorithms find utility ... on high-efficiency ...

In this paper, we propose a novel path loss model based on multi-dimensional Gaussian process regression (GPR) that gives spatial consistency to channels in propagation environment by predicting local ...

Here a machine learning algorithm will be trained to predict a liver disease in patients using a data-set collected from North East of Andhra Pradesh, India. Using machine learning models to predict ...

algorithm and the extreme learning machine (ELM), is proposed in this study, and the stresses of AZ80 magnesium alloy are predicted by the model through a 812-record dataset. The predicting results ...

It uses a pair of SRF linear accelerators ... trained a collection of machine learning surrogate models for each radiation detector and used an offline optimization algorithm to determine the ...