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, ...

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 ...

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 ...

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 ...

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 ...

In this paper, we used the composite vector with position conservation scoring function, increment of diversity and predictive secondary structure information as the input parameter of support vector ...

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