I found a question (Question 7) here:
Question: For k cross-validation, larger k value implies more bias
Options: True or False
My answer is: True.
Reason: Larger K means more folds means smaller test set which means larger training set. As you increase training data you bring down variance which means increase bias.
So as K increases --> Training data size increases --> Variance reduces --> Bias increases Hence answer is True
But the website says answer is False.
Can someone explain if my logic is wrong and why their answer is right?