leetcode347 - Top K Frequent Elements - medium

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.

 

共用部分是用map统计频次。接下来选出topk频次有variation。

1.O(nlogk), O(k). 堆。
写专属comparator,根据Entry<K, V>里的V也就是本题的频率排序,让堆顶始终维持是最小频率的元素,你最菜,当堆大小过k的时候把你挤走哦!

2.O(n), O(n). bucket sort。要用到频率最多也就是n的信息+O(n)的空间。
第一遍扫计算频率
第二遍扫根据频率把元素值放到对应frequency的bucket里。
第三遍扫bucket,从右往左(从高频到低频),凑满k个元素。
细节:
1.bucket因为不能保证某一频率只有一元素,所以要用List<Integer>[], generic type初始化特别,要List<Integer>[] buckets = new List[nums.length + 1];注意等号右边不带generic 

 

实现1:

class Solution {
    private class EntryComparator implements Comparator<Map.Entry<Integer, Integer>> {
        @Override
        // P2: 要过OJ要声明一下Map.Entry, 没办法只写Entry,因为不够普遍吧,没适配。
        public int compare(Map.Entry<Integer, Integer> a, Map.Entry<Integer, Integer> b) {
            return a.getValue() - b.getValue();
        }
    }
    
    public List<Integer> topKFrequent(int[] nums, int k) {
        Map<Integer, Integer> freqs = new HashMap<>();
        for (int num : nums) {
            freqs.put(num, freqs.getOrDefault(num, 0) + 1);
        }
        
        // 1.PQ
        PriorityQueue<Map.Entry<Integer, Integer>> minHeap = new PriorityQueue<>(new EntryComparator());
        for (Map.Entry<Integer, Integer> e : freqs.entrySet()) {
            minHeap.offer(e);
            if (minHeap.size() > k) {
                minHeap.poll();
            }
        }
        List<Integer> ans = new ArrayList<>();
        for (int i = 0; i < k; i++) {
            // P1:注意加到答案的是key不是entry
            ans.add(minHeap.poll().getKey());
        }
        Collections.reverse(ans);
        return ans;
    }
}

 

 

实现2:

class Solution {
    public List<Integer> topKFrequent(int[] nums, int k) {
        Map<Integer, Integer> freqs = new HashMap<>();
        for (int num : nums) {
            freqs.put(num, freqs.getOrDefault(num, 0) + 1);
        }
        
        // 1.bucket sort
        // P1: 注意这个初始化!
        List<Integer>[] buckets = new List[nums.length + 1];
        for (int num : freqs.keySet()) {
            int frequency = freqs.get(num);
            if (buckets[frequency] == null) {
                buckets[frequency] = new ArrayList<>();
            }
            buckets[frequency].add(num);
        }
        
        List<Integer> ans = new ArrayList<>();
        for (int i = buckets.length - 1; i >= 0; i--) {
            if (buckets[i] == null) {
                continue;
            }
            for (int j = 0; j < buckets[i].size() && k > 0; j++) {
                ans.add(buckets[i].get(j));
                k--;
            }
        }
        return ans;
    }
}

 

posted @ 2018-10-03 15:04  jasminemzy  阅读(180)  评论(0编辑  收藏  举报