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Solution 2: Dominant Occurrences

Approach Explanation

  1. Count the frequency of each element using a hash map.
  2. Use a min-heap to keep track of the k elements with the highest frequencies. The heap stores tuples of (frequency, element).

Step-by-Step Logic

  1. Use collections.Counter to get frequencies.
  2. Initialize a min-heap.
  3. For each (num, freq) pair in the counter:
    • Push (freq, num) to the heap.
    • If heap size > k, pop the smallest frequency element.
  4. Extract the num from each tuple in the heap and return as a list.

Complexity

  • Time Complexity: O(N log K), where N is the number of unique elements.
  • Space Complexity: O(N) for the count map.

Code

import heapq
from collections import Counter

def top_k_frequent(nums, k):
    counts = Counter(nums)
    # Min-heap of size k to keep track of top frequencies
    heap = []
    
    for val, freq in counts.items():
        heapq.heappush(heap, (freq, val))
        if len(heap) > k:
            heapq.heappop(heap)
            
    return [item[1] for item in heap]