Support Vector Machine is a versatile and powerful algorithm for classification and regression tasks. Its ability to handle high-dimensional data, its robustness to outliers, and its ability to learn ...

In order to solve the problem of low fault detection rate of combinatorial navigation due to the mismatch of support vector machine parameters, this paper uses genetic algorithm and lattice search ...

Welcome to the "Everything About Support Vector Machine (SVM) Machine Learning Algorithm" repository. In this repository, you will find a comprehensive collection of in-depth explanations, intuition, ...

Add a description, image, and links to the support-vector-machine-algorithm topic page so that developers can more easily learn about it. Curate this topic Add this topic to your repo ...

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 ...

A pioneering study reveals how archaeologists' satellite tools can be repurposed to tackle climate change. By using AI and satellite LiDAR imagery from NASA and ESA, researchers have found a faster, ...

Digital finance is accelerating, and threats are evolving in complexity, outpacing traditional methods for detecting fraud.

The Support Vector methods was proposed by V.Vapnik in 1965, when he was trying to solve problems in pattern recognition. In 1971, Kimeldorf proposed a method of constructing kernel space based on ...