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

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.

In this paper, a novel hybrid approach integrating genetic algorithm (GA) and support vector machines (SVM) is proposed to conduct the key factor exploration tasks in the core competitiveness ...

The support vector machine (SVM) algorithm is well known to the computer learning community for its very good practical results. The goal of the present paper is to study this algorithm from a ...

AI transforms RF engineering through neural networks that predict signal behavior and interference patterns, enabling ...

In this study, we address this methodological flaw by proposing the simultaneous application of support vector machine and probabilistic neural network (PNN)-based CDP algorithms, together with ...