347. 前 K 个高频元素
给你一个整数数组 nums
和一个整数 k
,请你返回其中出现频率前 k
高的元素。你可以按 任意顺序 返回答案。
输入: nums = [1,1,1,2,2,3], k = 2
输出: [1,2]
- topk (前k大)用小根堆,维护堆大小不超过 k 即可。每次压入堆前和堆顶元素比较,如果比堆顶元素还小,直接扔掉,否则压入堆。检查堆大小是否超过 k,如果超过,弹出堆顶。复杂度是 nlogk
- 避免使用大根堆,因为你得把所有元素压入堆,复杂度是 nlogn,而且还浪费内存。如果是海量元素,那就挂了。
- 求前 k 大,用小根堆,求前 k 小,用大根堆。
//引入快排,哈希表计算频率,排序后输出
import "sort"
func topKFrequent(nums []int, k int) []int {
m := make(map[int]int)
s := make([]int,0)
for _,v := range nums {
i,ok := m[v]
if ok {
m[v] = i+1
}else{
m[v] = 1
s = append(s, v)
}
}
sort.Slice(s, func(i, j int) bool {
return m[s[i]] > m[s[j]]
})
return s[:k]
}
//桶排序法,时空On
func topKFrequent(nums []int, k int) []int {
keymap:=make(map[int]int)
maxn:= math.MinInt64
for _,i:=range nums{
if _,ok:=keymap[i];ok{
keymap[i]++
}else{
keymap[i]=1
}
if keymap[i]>maxn{
maxn=keymap[i]
}
}
hashtop:=make([][]int,maxn+1)
for key,val:=range keymap{
hashtop[val]=append(hashtop[val],key)
}
res:=make([]int,0)
for i:=maxn;i>=0;i--{
res=append(res,hashtop[i]...)
k-=len(hashtop[i])
if k==0{
break
}
}
return res
}
官方解答:我也不会,排序太难了
//快排选择算法:平均时间On,空间On
func topKFrequent(nums []int, k int) []int {
occurrences := map[int]int{}
for _, num := range nums {
occurrences[num]++
}
values := [][]int{}
for key, value := range occurrences {
values = append(values, []int{key, value})
}
ret := make([]int, k)
qsort(values, 0, len(values) - 1, ret, 0, k)
return ret
}
func qsort(values [][]int, start, end int, ret []int, retIndex, k int) {
rand.Seed(time.Now().UnixNano())
picked := rand.Int() % (end - start + 1) + start;
values[picked], values[start] = values[start], values[picked]
pivot := values[start][1]
index := start
for i := start + 1; i <= end; i++ {
if values[i][1] >= pivot {
values[index + 1], values[i] = values[i], values[index + 1]
index++
}
}
values[start], values[index] = values[index], values[start]
if k <= index - start {
qsort(values, start, index - 1, ret, retIndex, k)
} else {
for i := start; i <= index; i++ {
ret[retIndex] = values[i][0]
retIndex++
}
if k > index - start + 1 {
qsort(values, index + 1, end, ret, retIndex, k - (index - start + 1))
}
}
}
//堆排:用小顶堆时间Nlogk,空间On;大顶堆Nlogn
func topKFrequent(nums []int, k int) []int {
occurrences := map[int]int{}
for _, num := range nums {
occurrences[num]++
}
h := &IHeap{}
heap.Init(h)
for key, value := range occurrences {
heap.Push(h, [2]int{key, value})
if h.Len() > k {
heap.Pop(h)
}
}
ret := make([]int, k)
for i := 0; i < k; i++ {
ret[k - i - 1] = heap.Pop(h).([2]int)[0]
}
return ret
}
type IHeap [][2]int
func (h IHeap) Len() int { return len(h) }
func (h IHeap) Less(i, j int) bool { return h[i][1] < h[j][1] }
func (h IHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *IHeap) Push(x interface{}) {
*h = append(*h, x.([2]int))
}
func (h *IHeap) Pop() interface{} {
old := *h
n := len(old)
x := old[n-1]
*h = old[0 : n-1]
return x
}