Support Vector Machines (SVMs) represent a robust and versatile class of machine learning algorithms that have significantly shaped the fields of pattern recognition, classification, and regression.

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 ...

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 ...

The support vector machine (SVM) is known for its good performance in two-class classification, but its extension to multiclass classification is still an ongoing research issue. In this article, we ...

He’s credited with coming up with the first support vector machine (SVM) algorithm. SVMs are widely used today for machine learning purposes.