StackedML
Practice
Labs
Questions
Models
Pricing
Sign in
Practice
/
Supervised Learning
/
Other Models
/
SVM (margin intuition, kernel trick)
SVM (margin intuition, kernel trick)
Margins and the kernel trick.
0/8
completed
1
2
3
4
5
6
7
8
easy
Definition of Support Vectors
2/8
What are support vectors in an SVM?
A
The feature vectors that span the directions of maximum variance in the training data
B
The training samples closest to the decision boundary that define and constrain the margin
C
The training samples that receive the highest weights during the optimization of the hinge loss
D
All training samples that are correctly classified by the decision boundary with nonzero confidence
Sign in to verify your answer