Lintcode: Majority Number 解题报告

Majority Number

原题链接：http://lintcode.com/en/problem/majority-number/#

Given an array of integers, the majority number is the number that occurs more than half of the size of the array. Find it.

Example

For [1, 1, 1, 1, 2, 2, 2], return 1

Challenge

O(n) time and O(1) space

SOLUTION 1:

http://www.geeksforgeeks.org/majority-element/

这里是一篇论文： http://www.cs.utexas.edu/~moore/best-ideas/mjrty/

这里用的算法是：MJRTY - A Fast Majority Vote Algorithm

1. 简单来讲，就是不断对某个议案投票，如果有人有别的议案，则将前面认为的议案的cnt减1，减到0换一个议案。

如果存在majority number，那么这个议案一定不会被减到0，最后会胜出。

2. 投票完成后，要对majority number进行检查，以排除不存在majority number的情况。如 1，2，3，4这样的数列，是没有majory number的。

很简单，统计一下结果议案的票数，没有过半就是没有majority number.

摘录一段解释：

METHOD 3 (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
Initialize:
maj_index = 0, count = 1 –> candidate ‘2?
2, 2, 3, 5, 2, 2, 6

Same as a[maj_index] => count = 2
2, 2, 3, 5, 2, 2, 6

Different from a[maj_index] => count = 1
2, 2, 3, 5, 2, 2, 6

Different from a[maj_index] => count = 0
Since count = 0, change candidate for majority element to 5 => maj_index = 3, count = 1
2, 2, 3, 5, 2, 2, 6

Different from a[maj_index] => count = 0
Since count = 0, change candidate for majority element to 2 => maj_index = 4
2, 2, 3, 5, 2, 2, 6

Same as a[maj_index] => count = 2
2, 2, 3, 5, 2, 2, 6

Different from a[maj_index] => count = 1

Finally candidate for majority element is 2.

First step uses Moore’s Voting Algorithm to get a candidate for majority element.

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"

 package Algorithms.lintcode.math;

 import java.util.ArrayList;

 public class MajorityNumber {
     /**
      * @param nums: a list of integers
      * @return: find a  majority number
      */
     public int majorityNumber(ArrayList<Integer> nums) {
         // write your code
         if (nums == null || nums.size() == 0) {
             // No majority number.
             return -1;
         }

         int candidate = nums.get(0);

         // The phase 1: Voting.
         int cnt = 1;
         for (int i = 1; i < nums.size(); i++) {
             if (nums.get(i) == candidate) {
                 cnt++;
             } else {
                 cnt--;
                 if (cnt == 0) {
                     candidate = nums.get(i);
                     cnt = 1;
                 }
             }
         }

         // The phase 2: Examing.
         cnt = 0;
         for (int i = 0; i < nums.size(); i++) {
             if (nums.get(i) == candidate) {
                 cnt++;
             }
         }

         // No majory number.
         if (cnt <= nums.size() / 2) {
             return -1;
         }

         return candidate;
     }
 }

2014.12.27 REDO:

 public int majorityElement(int[] num) {
         if (num == null || num.length == 0) {
             return -1;
         }

         int maj = num[0];

         int len = num.length;
         int cnt = 1;
         for (int i = 1; i < len; i++) {
             if (cnt == 0) {
                 maj = num[i];
                 cnt = 1;
             } else if (num[i] != maj) {
                 cnt--;
             } else {
                 cnt++;
             }
         }

         return maj;
     }

GITHUB:

https://github.com/yuzhangcmu/LeetCode_algorithm/blob/master/lintcode/math/MajorityNumber.java