A supervised machine learning algorithm that divides data into regions by drawing a best-fit boundary line into a “hyperplane” so that support vectors, which are the shortest line from the closest point perpendicular to the boundary line, are as large as they could possibly be. Support vector machines are simple and quick to train, requiring lower amounts of data and computing and best suited to problems such as sentiment analysis, binary classification, and simple predictive analytics.
Glossary of Artificial Intelligence (AI), Machine Learning (ML), and Big Data Terms
Support Vector Machine (SVM)
