Apply Operations to Maximize Frequency Score | Weekly Contest 376 | Leetcode 2968
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This is the 25th Video of our Playlist "Binary Search".
In this video we will try to solve a fantastic Binary Search problem - Apply Operations to Maximize Frequency Score (Leetcode 2968).
This problem falls under the category "Binary Search on Answer"
This was asked in Leetcode Weekly COntest - 376
I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.
Problem Name : Apply Operations to Maximize Frequency Score
Company Tags : will update soon
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Arrays/Binary%20Search/Apply%20Operations%20to%20Maximize%20Frequency%20Score.cpp
Leetcode Link : https://leetcode.com/problems/apply-operations-to-maximize-frequency-score/description/
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My Graph Concepts Playlist : https://youtu.be/5JGiZnr6B5w
My GitHub Repo for interview preparation : https://github.com/MAZHARMIK/Interview_DS_Algo
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Approach Summary (Binary Search on Answer) : The approach involves sorting the input vector nums and maintaining a prefix sum array prefix. The algorithm uses binary search to find the maximum frequency score that satisfies the given condition. The binary search is performed on the possible range of scores between min_score and max_score. The function IsPossible checks whether it is possible to achieve a certain frequency score by calculating the absolute differences between elements and their indices and comparing the total operations with the given limit k. The result is updated during the binary search, and the final maximum frequency score is returned. The time complexity of the solution is primarily determined by the sorting step (O(n log n)) and the binary search (O(log n)), resulting in an overall time complexity of O(n log n).
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✨ Timelines✨
00:00 - Introduction
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