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Best Case: If the list is sorted already then A[i] <= key at line 4. Thus, rest of the lines in the inner loop will not execute. Then,
T (n) = c1n + c2 (n -1) + c3(n -1) + c4 (n -1) = O (n), which indicates that the time complexity is linear.
Worst Case: This case arises while the list is sorted in reverse order. Thus, for execution of line 1, the Boolean condition at line 4 will be true.
So, step line 4 is executed
T (n) = c1n + c2(n -1) + c3(n -1) + c4 (n(n+1)/2 - 1) + c5(n(n -1)/2) + c6(n(n-1)/2) + c7 (n -1)
= O (n2).
Average case: In mostly cases, the list will be into some random order. That is, it neither sorted in descending or ascending order and the time complexity will lie somewhere among the best & the worst case.
T (n) best < T(n) Avg. < T(n) worst
Give example of assertion and abstract data type For illustration, consider Natural ADT whose carrier set is the set of non-negative integers and whose operations are the usual
Q. Make the 11 item hash table resulting from hashing the given keys: 12, 44, 13, 88, 23, 94, 11, 39, 20, 16 and 5 by making use of the hash function h(i) = (2i+5) mod 11.
I am looking for some help with a data mining class with questions that are about neural networks and decision trees. Can you help? I can send document with questions.
#What is the pointer
#question.show that the following inequality is correct or incorrect. n!=O(n^n)
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