Support Vector Machine

A supervised machine learning algorithm used for classification and regression tasks. SVMs work by finding the optimal hyperplane that separates data points into distinct categories in a high-dimensional feature space. In accessibility research, SVMs have been used to detect dyslexia from eye tracking data, classify assistive technology usage patterns, and automate accessibility evaluation. Their ability to handle binary classification tasks makes them particularly useful for distinguishing between user groups, such as readers with and without dyslexia based on eye movement measures.