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...
Given a non-empty array of integers, return thekmost frequent elements. For example, Given[ 1,1,1,2,2,3]and k = 2, return[1,2]. Note: You may assumekis always valid, 1 ≤k≤ number of unique elements. Your algorithm's time complexity must be better than O(nlogn), wherenis ...
https://leetcode.com/problems/top-k-frequent-elements/ https://leetcode.com/problems/top-k-frequent-elements/discuss/81602/Java-O(n)-Solution-Bucket-Sort https://leetcode.com/problems/top-k-frequent-elements/discuss/81635/3-Java-Solution-using-Array-MaxHeap-TreeMap LeetCode All in One 题目...
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 Output: [1,2] Example 2: Input:nums = [1], k = 1Output:[1] Note: You may assumekis always valid...
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) ,空间复杂度为 O(n)...
Leetcode 347.Top K Frequent Elements Given a non-empty array of integers, return the k most frequent elements. 题目链接:Top K Frequent Elements 一句话理解题意:输出数组中出现次数对多的k个数。 在如果用C语言来写这个题目,思路就是先按数的大小排序,然后再用一个结构体数组保存每个...
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....
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]...
Mining top-k regular-frequent itemsets from transactional databaseKomate Amphawan
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 ...