Is Minimum Score by Changing Two Elements easy or hard?

The problem is classified as Medium on LeetCode. The challenge is recognizing that changing two elements effectively removes two extremes that expand the range. Once that insight is clear, the implementation becomes straightforward after sorting.

Minimum Score by Changing Two Elements Python/Java solution

In Python or Java, sort the array first, then compute the minimum among three expressions: nums[n-3] - nums[0], nums[n-2] - nums[1], and nums[n-1] - nums[2]. The same logic works across languages including C++, C#, and JavaScript because it only depends on sorting and index access.

How to solve Minimum Score by Changing Two Elements in O(n)?

A strict O(n) solution is generally not used because identifying extreme ordering without sorting is harder than necessary. Sorting the array in O(n log n) already provides a simple and reliable solution. Once sorted, evaluating the three candidate ranges takes constant time.

What is the best approach for Minimum Score by Changing Two Elements?

The best approach sorts the array and checks three possible scenarios: remove the two largest elements, remove the two smallest elements, or remove one from each side. After sorting, compute nums[n-3] - nums[0], nums[n-2] - nums[1], and nums[n-1] - nums[2]. The minimum of these values is the optimal score. The time complexity is O(n log n) due to sorting and O(1) extra space.

Is Minimum Score by Changing Two Elements asked at Google/Amazon/Meta?

Problems that involve minimizing ranges by modifying elements appear frequently in interviews at companies like Amazon, Google, and Meta. The specific LeetCode problem may vary, but the greedy insight of removing extreme values after sorting is a common interview pattern.

What data structure is used in Minimum Score by Changing Two Elements?

The solution primarily relies on arrays and sorting. After sorting, simple index access retrieves the smallest and largest elements needed to evaluate the three possible scenarios. No additional complex data structures are required.

What is the time complexity of Minimum Score by Changing Two Elements?

The optimal solution runs in O(n log n) time because the array must be sorted first. After sorting, only three constant-time comparisons are required to evaluate the possible ranges. Space complexity is O(1) if sorting is done in place.

Description Hints 2 Solution Video 3:48

2567. Minimum Score by Changing Two Elements

Medium50.4% acceptance

You are given an integer array nums.

The low score of nums is the minimum absolute difference between any two integers.
The high score of nums is the maximum absolute difference between any two integers.
The score of nums is the sum of the high and low scores.

Return the minimum score after changing two elements of nums.

Example 1:

Input: nums = [1,4,7,8,5]

Output: 3

Explanation:

Change nums[0] and nums[1] to be 6 so that nums becomes [6,6,7,8,5].
The low score is the minimum absolute difference: |6 - 6| = 0.
The high score is the maximum absolute difference: |8 - 5| = 3.
The sum of high and low score is 3.

Example 2:

Input: nums = [1,4,3]

Output: 0

Explanation:

Change nums[1] and nums[2] to 1 so that nums becomes [1,1,1].
The sum of maximum absolute difference and minimum absolute difference is 0.

Constraints:

3 <= nums.length <= 10⁵
1 <= nums[i] <= 10⁹

Topics

Hints open one at a time

Hint 1

Changing the minimum or maximum values will only minimize the score.

Hint 2

Think about what all possible pairs of minimum and maximum values can be changed to form the minimum score.

3:48

Still stuck?Read 3 approaches, or watch a walkthrough.

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1class Solution:
2    def minimizeSum(self, nums: List[int]) -> int:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2

Input

[1,4,7,8,5]

Input

[1,4,3]

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