Question

There are 77 rows of Berkeley students and 23 rows of Stanford students in the coordinates table. If we used the entire coordinates table as the training set, what is the smallest value of k that would ensure that a k-Nearest Neighbor classifier would always predict Berkeley as the class?

Answer 1

The smallest value of k that ensures a k-NN classifier predicts 'Berkeley' as the class is 24, which is one more than the total Stanford student rows.

Step-by-step explanation:

The question pertains to a machine learning technique called k-Nearest Neighbors (k-NN). In the given scenario, to ensure that a k-NN classifier always predicts 'Berkeley' as the class, you would need to choose a value of k that is larger than the number of rows of Stanford students in the training set.

Since there are 23 rows of Stanford students, the smallest k value that would ensure 'Berkeley' is always the predicted class is 24 (which is one more than the number of Stanford students), assuming there are no ties to resolve.