Support Vector Machines (SVMs) are methods used in Supervised learning, applied mainly to classification tasks.
SVMs try to find the most optimal separation line/plane between classes in a vector space.
Support Vectors are observations/data samples that are located in the Soft margin of that classification.
- Keywords: machine-learning
- [b] Support Vector Classifiers (the baby SVMs)
- [b] Kernel functions, e.g. polynomial and radial functions + Kernel tricks