In order to accurately build the learner's learning style in E-Learning, according to the needs and preferences to provide personalized learning materials and harmonious human-computer interaction ...

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 ...

The most robust machine learning (ML) method for nonlinear data classification, called support vector machines (SVMs), has been used for the classification of faults in intricate industrial processes.

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 ...

The purpose is to explore the feature recognition, diagnosis, and forecasting performances of Semi-Supervised Support Vector Machines (S3VMs) for brain image fusion Digital Twins (DTs). Both unlabeled ...

These techniques include Artificial Neural Network (ANN), Numerical Rationale (NR), Support Vector Machine (SVM), Molecule Swarm Improvement (MSI), etc. Among these models, ANN and SVM models have ...

Introduction to Support Vector Machines. Support Vector Machines (SVMs) are supervised learning models for classification and regression problems.