I would like to know how min heap is used here to solve the following problem.
What I thought to solve it is to use hashtable and save the counts of the numbers. but I don't know how to use the min heap to contiune solving the problem.
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 n), where n is the array's size.
vector<int> topKFrequent(vector<int>& nums, int k) {
unordered_map<int, int> counts;
priority_queue<int, vector<int>, greater<int>> max_k;
for(auto i : nums) ++counts[i];
for(auto & i : counts) {
max_k.push(i.second);
// Size of the min heap is maintained at equal to or below k
while(max_k.size() > k) max_k.pop();
}
vector<int> res;
for(auto & i : counts) {
if(i.second >= max_k.top()) res.push_back(i.first);
}
return res;
}
The code works like this:
for(auto i : nums) ++counts[i]; // Use a map to count how many times the
// individual number is present in input
priority_queue<int, vector<int>, greater<int>> max_k; // Use a priority_queue
// which have the smallest
// number at top
for(auto & i : counts) {
max_k.push(i.second); // Put the number of times each number occurred
// into the priority_queue
while(max_k.size() > k) max_k.pop(); // If the queue contains more than
// k elements remove the smallest
// value. This is done because
// you only need to track the k
// most frequent numbers
vector<int> res; // Find the input numbers
for(auto & i : counts) { // which is among the most
if(i.second >= max_k.top()) res.push_back(i.first); // frequent numbers
// by comparing their
// count to the lowest of
// the k most frequent.
// Return numbers whose
// frequencies are among
// the top k
EDIT
As pointed out by @SergeyTachenov here How min heap is used here to solve this, your result vector may return more than k elements. Maybe you can fix that by doing:
for(auto & i : counts) {
if(i.second >= max_k.top()) res.push_back(i.first);
if (res.size() == k) break; // Stop when k numbers are found
}
Another small comment
You don't really need a while
-statement here:
while(max_k.size() > k) max_k.pop();
an if
-statement would do.