Given a non-empty array of integers, return the k most frequent elements.
Example 1:
Input: nums = [1,1,1,2,2,3], k = 2
Output: [1,2]
Example 2:
Input: nums = [1], k = 1
Output: [1]
Note:
- You may assume k is always valid, 1 ≤ k ≤ number of unique elements.
- Your algorithm’s time complexity must be better than O(n log n), where n is the array’s size.
python一行解法:
class Solution:
def topKFrequent(self, nums: List[int], k: int) -> List[int]:
return [key for key, value in collections.Counter(nums).most_common(k)]
java官方解法:
class Solution {
public List<Integer> topKFrequent(int[] nums, int k) {
// build hash map : character and how often it appears
HashMap<Integer, Integer> count = new HashMap();
for (int n: nums) {
count.put(n, count.getOrDefault(n, 0) + 1);
}
// init heap 'the less frequent element first'
PriorityQueue<Integer> heap =
new PriorityQueue<Integer>((n1, n2) -> count.get(n1) - count.get(n2));
// keep k top frequent elements in the heap
for (int n: count.keySet()) {
heap.add(n);
if (heap.size() > k)
heap.poll();
}
// build output list
List<Integer> top_k = new LinkedList();
while (!heap.isEmpty())
top_k.add(heap.poll());
Collections.reverse(top_k);
return top_k;
}
}
有一个比官方解答快3倍的Java解法:
class Solution {
public List<Integer> topKFrequent(int[] nums, int k) {
List<Integer>[] bucket = new List[nums.length + 1];
Map<Integer, Integer> frequencyMap = new HashMap<Integer, Integer>();
for (int n : nums) {
frequencyMap.put(n, frequencyMap.getOrDefault(n, 0) + 1);
}
for (int key : frequencyMap.keySet()) {
int frequency = frequencyMap.get(key);
if (bucket[frequency] == null) {
bucket[frequency] = new ArrayList<>();
}
bucket[frequency].add(key);
}
List<Integer> res = new ArrayList<>();
for (int pos = bucket.length - 1; pos >= 0 && res.size() < k; pos--) {
if (bucket[pos] != null) {
res.addAll(bucket[pos]);
}
}
return res;
}
}

本文提供了一种高效算法来找出数组中出现频率最高的k个元素,并给出了Python和两种Java实现方案。
1193

被折叠的 条评论
为什么被折叠?



