About this document
Understanding Support Vector Machines by jovita is a document available to read on EtoBox.
Support Vector Machine (SVM) is a popular supervised learning algorithm primarily used for classification, aiming to create the best decision boundary, or hyperplane, to segregate data points. It utilizes support vectors, which are the closest data points to the hyperplane, to maximize the margin between different classes. SVM can be linear or non-linear, depending on whether the data can be separated by a straight line or requires additional dimensions for classification.
- Author
- jovita
- Language
- EN