169. Majority Element

Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊ n/2 ⌋ times.

You may assume that the array is non-empty and the majority element always exist in the array.

Example 1:

Input: [3,2,3]
Output: 3

Example 2:

Input: [2,2,1,1,1,2,2]
Output: 2

class Solution {
    public int majorityElement(int[] nums) {
        Arrays.sort(nums);
        return(nums[nums.length/2]);
     }
}

既然超过n/2次，那排序完成后肯定中间的element就是要求的。

class Solution {
    public int majorityElement(int[] nums) {
        // Arrays.sort(nums);
        // return(nums[nums.length/2]);
        int res = nums[0], count=1;
        for(int i =1; i < nums.length; i++){     
            if(nums[i] == res){
                count++;
            }
            else{
                count--;
            }
            if(count<=0) {res = nums[i];
                         count=1;}
        }
        return res;
     }
}

摩尔投票法，先将第一个数字假设为众数，然后把计数器设为1，比较下一个数和此数是否相等，若相等则计数器加一，反之减一。然后看此时计数器的值，若为零，则将下一个值设为候选众数。以此类推直到遍历完整个数组，当前候选众数即为该数组的众数。

原理：超过半数的数一定能抵消掉所有别的数然后存活下来。

class Solution {
    public int majorityElement(int[] nums) {
        // Arrays.sort(nums);
        // return(nums[nums.length/2]);
        // int res = nums[0], count=1;
        // for(int i =1; i < nums.length; i++){     
        //     if(nums[i] == res){
        //         count++;
        //     }
        //     else{
        //         count--;
        //     }
        //     if(count<=0) {res = nums[i];
        //                  count=1;}
        // }
        // return res;
         Map<Integer, Integer> counts = new HashMap<Integer, Integer>();
         for (int num : nums) {
            if (!counts.containsKey(num)) {
                counts.put(num, 1);
            }
            else {
                counts.put(num, counts.get(num)+1);
            }
        }
      for(Map.Entry<Integer,Integer> me : counts.entrySet()){
          if(me.getValue() > nums.length/2) return me.getKey();
      }
        return -1;
     }
}

HashMap.