Answer:
There is also an attachment below
Explanation:
Since we are talking about binary search, let's assume that the items are sorted according to some criteria.
Time complexity of binary search is O(logN) in worst case, best case and average case as well. That means it can search for an item in Log N time where N is size of the input. Here problem talks about the item not getting found. So, this is a worst case scenario. Even in this case, binary search runs in O(logN) time.
N = 700000000.
So, number of comparisions can be log(N) = 29.3 = 29.
So, in the worst case it does comparisions 29 times
Ithink that the answer is C)
Answer:
Theoretically Yes
Explanation:
The data given is linearly separable. So, the subset of the data will also be linearly separable. And it will pass for all training dataset. However, you should definitely never expect such thing In any real-life problem because the data is noisy, for a bazilion of reasons, so no model is guaranteed to perform perfectly.
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