Which term designates the set of data points that lie closest to the boundary in a classifier?

Which term designates the set of data points that lie closest to the boundary in a classifier?

• A. Margin
• B. Support Vectors
• C. Boundary
• D. Nearest Points

Answer: (B)

In a classifier like a support vector machine, the data points that lie closest to the decision boundary are called support vectors. They sit on the edge of the margin and are the critical points that define the position and orientation of the boundary. The learning process focuses on maximizing the margin, which is the distance from the boundary to these closest points; the boundary itself is the separating hyperplane. While the term “nearest points” describes their intuition, the standard terminology used is support vectors.

In a classifier like a support vector machine, the data points that lie closest to the decision boundary are called support vectors. They sit on the edge of the margin and are the critical points that define the position and orientation of the boundary. The learning process focuses on maximizing the margin, which is the distance from the boundary to these closest points; the boundary itself is the separating hyperplane. While the term “nearest points” describes their intuition, the standard terminology used is support vectors.