A supervised learning model that finds the boundary between classes of data that leaves the widest possible margin to the nearest data points of each class, effective on data with many features relative to the number of examples.
Facts
Core PrincipleA supervised max-margin model that separates classes with the widest margin. 1 Connections
Associated With
In Field
Invented
Corinna Cortes co-developed the soft-margin support vector machine with Vladimir Vapnik, published in their 1995 paper.
Vladimir Vapnik co-developed the soft-margin support vector machine with Corinna Cortes, published in their 1995 paper.
Sources
1. Support vector machine - Wikipedia
Section: History
The original SVM algorithm was invented by Vladimir N. Vapnik and Alexey Ya. Chervonenkis in 1964.
Lead paragraph
a support vector machine (SVM) or support vector network is a supervised max-margin model with associated learning algorithms that analyze data for classification and regression analysis.
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