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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, ...
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 ...
Discover the importance of protein structure prediction and the accurate method used in this study. Achieve a 95.6% overall prediction accuracy for β-turn types in protein chains.
Overview: This project is an implementation of a Support Vector Machine (SVM) algorithm for classification tasks. Support Vector Machines are powerful supervised learning models used for ...
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 ...