Support Vector Machine (SVM)
A support vector machine is a supervised learning model that classifies data by finding the boundary that separates classes with the widest possible margin.
What is Support Vector Machine (SVM)?
SVMs were among the leading machine learning methods before deep learning and are still used for smaller datasets such as text categorisation. Kernel functions let them draw curved boundaries.
How it works
The algorithm finds the boundary that maximises the distance to the nearest training points of each class, called support vectors.
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