What is the time complexity of Minimum Deletions to Make Character Frequencies Unique?

The optimal solution for Minimum Deletions to Make Character Frequencies Unique runs in O(n log n) time and uses O(n) space. The time complexity is O(n log n) due to sorting the frequency list, while the space complexity is O(n) for storing the frequency counts.

What is the brute force solution for Minimum Deletions to Make Character Frequencies Unique?

The brute force approach for Minimum Deletions to Make Character Frequencies Unique is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute-force approach involves generating all possible substrings of the input string and checking if their character frequencies are unique. This method is straightforward but inefficient for larger strings. The optimal Optimal Solution approach improves this to O(n log n).

What algorithm or data structure is used to solve Minimum Deletions to Make Character Frequencies Unique?

Minimum Deletions to Make Character Frequencies Unique uses the following concepts: Hash Table, String, Greedy, Sorting. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Minimum Deletions to Make Character Frequencies Unique?

Always discuss your thought process and approach before coding. Consider edge cases and constraints while explaining your solution. Practice explaining your code as you write it to simulate interview conditions.

What are common mistakes when solving Minimum Deletions to Make Character Frequencies Unique?

Not considering the case where all characters are already unique. Failing to handle the decrementing of frequencies properly.

#1647

Minimum Deletions to Make Character Frequencies Unique

Medium

Hash TableStringGreedySortingHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n log n)
Space	O(1)	O(n)

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Intuition

Time O(n log n)Space O(n)

The optimal solution leverages a frequency count of characters and a greedy approach to ensure frequencies are unique by decrementing duplicates. This is efficient and avoids unnecessary computations.

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Algorithm

4 steps

1Step 1: Count the frequency of each character in the string.
2Step 2: Store these frequencies in a list and sort it in descending order.
3Step 3: Iterate through the sorted frequencies and ensure each frequency is unique by decrementing duplicates and counting the deletions needed.
4Step 4: Return the total number of deletions.

solution.py15 lines

1# Full working Python code
2from collections import Counter
3
4def min_deletions_optimal(s):
5    freq = Counter(s)
6    freq_values = sorted(freq.values(), reverse=True)
7    deletions = 0
8    seen = set()
9    for f in freq_values:
10        while f in seen and f > 0:
11            f -= 1
12            deletions += 1
13        seen.add(f)
14    return deletions
15

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Complexity note: The time complexity is O(n log n) due to sorting the frequency list, while the space complexity is O(n) for storing the frequency counts.

1Character frequencies must be unique to make the string good.
2Using a greedy approach allows us to minimize deletions efficiently.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.