Q291
Suppose we train a hard-margin linear SVM on n > 100 data points in R2, yielding a hyperplane with exactly 2 support vectors. If we add one more data point and retrain the classifier, what is the maximum possible number of support vectors for the new hyperplane (assuming the n + 1 points are linearly separable)?
A.
2
B.
3
C.
n
D.
n+1
AnswerAnswer: Option D
Solution
Answer: Option D
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