Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Incremental learning is one of the most effective methods of learning accumulated data and large-scale data. The newly increased samples of the previously known works on incremental learning are ...

In order to accurately and effectively diagnose the transmission line faults of the power system, a genetic-algorithm support vector machine and the D-S evidence theory based fault diagnostic model is ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

Scientists from the Ivcher Institute for Brain, Cognition, and Technology (BCT Institute) at Reichman University (IDC Herzliya) explored a largely unrecognized perceptual ability and utilized machine ...

Five groups of different feature inputs are constructed based on the cumulative feature importance, and the original support vector machine regression (SVR) algorithm is applied to perform SOH ...

Abstract The manuscript presents an augmented Lagrangian—fast projected gradient method (ALFPGM) with an improved scheme of working set selection, pWSS, a decomposition based algorithm for training ...