Suppose we train a hard-margin linear SVM on n 100 data...

Home / Computer Science / Machine Learning / Question

Examveda

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

Answer: Option D

This Question Belongs to Computer Science >> Machine Learning

Related Questions on Machine Learning

A. training based on historical data

B. prediction to answer a query

C. both A and B

D. automization of complex tasks

View Answer

A. scalable

B. accuracy

C. fast

D. all of the above

View Answer

A. machine learning model

B. machine learning algorithm

C. null

D. accuracy

View Answer

A. data mining.

B. artificial intelligence

C. big data computing

D. internet of things

View Answer