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This approach uses a hash map to count the frequency of each element. We then use a min-heap to keep track of the top k elements.
Time Complexity: O(n log n) due to sorting.
Space Complexity: O(n) for storing frequencies.
1import java.util.*;
2
3class Solution {
4 public int[] topKFrequent(int[] nums, int k) {
5 Map<Integer, Integer> freqMap = new HashMap<>();
6 for (int num : nums) {
7 freqMap.put(num, freqMap.getOrDefault(num, 0) + 1);
8 }
9
10 PriorityQueue<Integer> minHeap = new PriorityQueue<>((a, b) -> freqMap.get(a) - freqMap.get(b));
11 for (int num : freqMap.keySet()) {
12 minHeap.add(num);
13 if (minHeap.size() > k) {
14 minHeap.poll();
15 }
16 }
17
18 int[] result = new int[k];
19 for (int i = k - 1; i >= 0; i--) {
20 result[i] = minHeap.poll();
21 }
22 return result;
23 }
24
25 public static void main(String[] args) {
26 Solution sol = new Solution();
27 int[] nums = {1,1,1,2,2,3};
28 int k = 2;
29 int[] result = sol.topKFrequent(nums, k);
30 System.out.println(Arrays.toString(result));
31 }
32}
33HashMap is used to record the frequency of each element, and a min heap of size k keeps track of the top k elements based on frequency.
This approach involves using bucket sort where we create buckets for frequency counts and then extract the top k frequent elements.
Time Complexity: O(n + k).
Space Complexity: O(n).
1#include <iostream>
2#include <vector>
#include <unordered_map>
#include <algorithm>
using namespace std;
vector<int> topKFrequent(vector<int>& nums, int k) {
unordered_map<int, int> freqMap;
vector<vector<int>> buckets(nums.size() + 1);
for (int num : nums) {
freqMap[num]++;
}
for (auto& p : freqMap) {
buckets[p.second].push_back(p.first);
}
vector<int> result;
for (int i = buckets.size() - 1; i >= 0 && result.size() < k; --i) {
for (int num : buckets[i]) {
result.push_back(num);
if (result.size() == k) break;
}
}
return result;
}
int main() {
vector<int> nums = {1, 1, 1, 2, 2, 3};
int k = 2;
vector<int> result = topKFrequent(nums, k);
for (int num : result) {
cout << num << " ";
}
return 0;
}
Frequency occurrences are placed in buckets. The largest buckets represent the most frequent elements.