169.Majority Element
Description
#169 | Majority Element | Easy | ||
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Array | Top 150 | |||
Given an array nums of size n, return the majority element.. |
The majority element is the element that appears more than ⌊n / 2⌋ times. You may assume that the majority element always exists in the array.
Example 1:
Input: nums = [3,2,3]
Output: 3
Example 2:
Input: nums = [2,2,1,1,1,2,2]
Output: 2
HashMap
Runtime 12ms |
|
Memory 49.68MB |
|
class Solution {
public int majorityElement(int[] nums) {
Map<Integer, Integer> counts = new HashMap<>();
float half = nums.length / 2.0f;
for(int i = 0; i < nums.length; i++) {
int count = counts.getOrDefault(nums[i], 0) + 1;
if(count > half) return nums[i];
counts.put(nums[i], count);
}
throw new RuntimeException("No majority element found");
}
}
Sort and return middle
The element must be at n/2 after sorted!
Runtime 5ms |
|
Memory 53.59MB |
|
class Solution {
public int majorityElement(int[] nums) {
Arrays.sort(nums);
return nums[nums.length / 2];
}
}
Bit Manipulation
For each number, if it's the majority, then each bit must also be the majority!
5 5 2 1 2 2 2 =>
1 0 1
1 0 1
0 1 0
0 0 1
0 1 0
0 1 0
0 1 0
Runtime 6ms |
|
Memory 52.97MB |
|
class Solution {
public int majorityElement(int[] nums) {
int n = nums.length, ans = 0;
int half = n / 2;
for(int i = 0; i < 32; i++) {
int count = 0, mask = 1 << i;
for(int j = 0; j < n; j++) {
if((nums[j] & mask) == mask)
count ++;
}
if(count > half) ans |= 1 << i;
}
return ans;
}
}
Boyer-Moore Majority Vote Algorithm
Runtime 1ms |
|
Memory 53.97MB |
|
class Solution {
public int majorityElement(int[] nums) {
int element = 0, count = 0;
for(int i = 0; i < nums.length; i++) {
if(count == 0) {
count = 1;
element = nums[i];
continue;
}
if(nums[i] == element) count ++;
else count --;
}
return element;
}
}