A majority element in an array A[] of size n is an element that appears more than n/2 times (and hence there is at most one such element). Write a function which takes an array and emits the majority element (if it exists), otherwise prints NONE as follows: I/P : 3 3 4 2 4 4 2 4 4 O/P : 4 I/P : 3 3 4 2 4 4 2 4 O/P : NONE Using Moore’s Voting Algorithm: This is a two step process. 1. Get an element occurring most of the time in the array. This phase will make sure that if there is a majority element then it will return that only. 2. Check if the element obtained from above step is majority element. 1. Finding a Candidate: The algorithm for first phase that works in O(n) is known as Moore’s Voting Algorithm. Basic idea of the algorithm is if we cancel out each occurrence of an element e with all the other elements that are different from e then e will exist till end if it is a majority element. findCandidate(a[], size) 1. Initialize index and count of majority element maj_index = 0, count = 1 2. Loop for i = 1 to size – 1 (a)If a[maj_index] == a[i] count++ (b)Else count--; (c)If count == 0 maj_index = i; count = 1 3. Return a[maj_index] Above algorithm loops through each element and maintains a count of a[maj_index], If next element is same then increments the count, if next element is not same then decrements the count, and if the count reaches 0 then changes the maj_index to the current element and sets count to 1. First Phase algorithm gives us a candidate element. In second phase we need to check if the candidate is really a majority element. Second phase is simple and can be easily done in O(n). We just need to check if count of the candidate element is greater than n/2. Example : A[] = 2, 2, 3, 5, 2, 2, 6 , answer : 2. 2. Check if the element obtained in step 1 is majority printMajority (a[], size) 1. Find the candidate for majority 2. If candidate is majority. i.e., appears more than n/2 times. Print the candidate 3. Else Print "NONE"
Saturday, September 3, 2011
Majority Element
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