Brilliant Market Share Analysis for June 2026

Support vector machines are a supervised learning method used to perform binary classification on data. They are motivated by the principle of optimal separation, the idea that a good classifier finds the largest gap possible between data points of different classes. For example, an algorithm learning to separate the United States from Europe on a map could correctly learn a boundary 100 miles off the eastern shore of the United States, but a much …