Description
Detailed description
Detailed description:
Problem Statement:
The Moore Voting Algorithm is an efficient way to find the majority element in an array. A majority element is defined as an element that appears more than n/2 times in the array, where n is the length of the array. The algorithm works in two phases:
Candidate Selection: Traverse the array and choose a candidate for the majority element by maintaining a count. When the count reaches zero, a new candidate is selected.
Verification: Verify that the candidate is indeed the majority element by counting its occurrences in a second pass through the array.
The algorithm has a time complexity of O(n) and a space complexity of O(1).
Context
This algorithm is important in scenarios where the majority element needs to be identified efficiently, such as in voting systems or stream processing applications. The typical brute-force or sorting approaches have higher time complexities, whereas Moore Voting Algorithm is optimal for this type of problem.
This change benefits users who are working on algorithms that involve large datasets, providing them with a more efficient solution for finding a dominant or majority element in a list or array.
Possible implementation
Possible implementation:
The Moore Voting Algorithm can be implemented with the following steps:
-
Initialize a variable candidate to store the current candidate and a variable count to track the candidate’s occurrences.
-
Traverse the array, adjusting the candidate and count.
-
Verify by making a second pass through the array to check if the selected candidate appears more than n / 2 times.
Test Case Example:
Input:
[3, 3, 4, 2, 4, 4, 2, 4, 4]
Expected Output:
Majority Element: 4
Additional information
No response