代码(Python3) class Solution: def topKFrequent(self, nums: List[int], k: int) -> List[int]: # 统计 nums 中每个数字出现的次数, # 时间复杂度为 O(n) ,空间复杂度为 O(n) num_to_cnt = Counter(nums) #将 num_to_cnt 中的数字及其出现次数收集到数组中, # 时间复杂度为 O(n) ,空间...
LeetCode Given a non-empty array of integers, return thekmost frequent elements. Example 1: Input: nums = [1,1,1,2,2,3], k = 2Output: [1,2] Example 2: Input: nums = [1], k = 1Output: [1] Note: You may assumekis always valid, 1 ≤k≤ number of unique elements. Your ...
Note: You may assumekis always valid, 1 ≤k≤ number of unique elements. Your algorithm's time complexity must be better than O(nlogn), wherenis the array's size. https://leetcode.com/problems/top-k-frequent-elements/ 求出现频率最高的K个数,要求时间复杂度不能超过 O(nlogn)。 选择最...
之后,我们返回 items 列表中的前 k个元组的key即可。 3 Python 解题代码 其实小根堆也可以结合 Counter 字典(官方解法一:哈希表+排序),所以我们先演示 Counter。 3.1 Counter - 哈希表+排序 解题代码 ## LeetCode 692E - The K Frequent Word - Counter,字典数据结构fromtypingimportListfromcollectionsimportCoun...
Given a non-empty array of integers, return thekmost 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. ...
Given a non-empty array of integers, return the k most frequent elements. For example, Given [1,1,1,2,2,3] and k = 2, return [1,2]. 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...
347. Top K Frequent Elements 前 K 个高频元素,给定一个非空的整数数组,返回其中出现频率前 k 高的元素。 示例1:输入:nums=[1,1,1,2,2,3],k=2输出:[1,2]示例2:输入:nums=[1],k=1输出:[1] 提示:你可以假设给定的 k 总是合理的,且1≤k≤数组中不相同的元素的个数。你的算
347. Top K Frequent Elements 阿团相信梦想都能实现关注IP属地: 加州 2016.08.23 05:36:14字数 0阅读 203 importcollectionsclassSolution(object):deftopKFrequent(self,nums,k):""" :type nums: List[int] :type k: int :rtype: List[int] """return[keyforkey,_incollections.Counter(nums).most_...
Many big data applications today require querying highly dynamic and large-scale data streams for top-k frequent items in the most recent window of any specified size at any time. This is a challenging problem. We show that our novel solution is not only accurate, but it also one to two ...
Top-k frequent itemsItem frequency trackingSliding windowMany big data applications today require querying highly dynamic and large-scale data streams to find the top-k most frequent items in the most recent window of a specified size at a specific time. This is a challenging problem. We ...