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...
leetcode 347. 前K个高频元素(Top K Frequent Elements) 目录 题目描述: 示例1: 示例2: 解法: 题目描述: 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] 说明: ...
classSolution(object):deftopKFrequent(self, nums, k):"""Given a non-empty array of integers, return the k most frequent elements. heapq.nlargest(n, iterable[, key]) Return a list with the n largest elements from the dataset defined by iterable."""count=collections.Counter(nums)returnheapq...
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. 分析 题目的意思是:求一个数组里面前k个频繁元素。 首先建立一个map,然后将map的key value值互换,放进桶里面,然后逆转...
原题链接 :https://leetcode.com/problems/top-k-frequent-elements/ Given a non-empty array of integers, return thekmost frequent elements. 给定一个不为空的数字数组,返回出现频率最高的k个元素。 Example 1: Input: nums = [1,1,1,2,2,3], k = 2 ...
heappop(heap)[1] for _ in range(k)] 代码(Go) func topKFrequent(nums []int, k int) []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) numToCnt := make(map[int]int) for _, num := range nums { // num 如果不在 num_to_cnt 中,则...
347. Top K Frequent Elements 问题描述 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]...
347. Top K Frequent Elements Given a non-empty array of integers, return the k most frequent elements. For example, Given[1,1,1,2,2,3]andk=2,return[1,2]. Note: You may assume k is always valid, 1 ? k ? number of unique elements....
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 ...
We propose an integrated approach for solving both problems of finding the most popular k elements, and finding frequent elements in a data stream. Our technique is efficient and exact if the alphabet under consideration is small. In the more practical large alphabet...Metwally, Ahmed...