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HomeLeetCode ProblemsFind Weighted Median Node in Tree
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How to Solve Find Weighted Median Node in Tree Problem

Master the Find Weighted Median Node in Tree LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.

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Hard#3585
LeetCode Problem

Find Weighted Median Node in Tree

You are given an integer n and an undirected, weighted tree rooted at node 0 with n nodes numbered from 0 to n - 1. This is represented by a 2D array edges of length n - 1, where edges[i] = [ui, vi, wi] indicates an edge from node ui to vi with weight wi. The weighted median node is defined as the first node x on the path from ui to vi such that the sum of edge weights from ui to x is greater than or equal to half of the total path weight. You are given a 2D integer array queries. For each queries[j] = [uj, vj], determine the weighted median node along the path from uj to vj. Return an array ans, where ans[j] is the node index of the weighted median for queries[j].

ArrayBinary SearchDynamic ProgrammingTreeDepth-First Search

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Problem Breakdown

Understanding the Find Weighted Median Node in Tree Problem

Let's break down this LeetCode problem and understand what makes it challenging in interview settings.

Problem Statement

You are given an integer n and an undirected, weighted tree rooted at node 0 with n nodes numbered from 0 to n - 1. This is represented by a 2D array edges of length n - 1, where edges[i] = [ui, vi, wi] indicates an edge from node ui to vi with weight wi. The weighted median node is defined as the first node x on the path from ui to vi such that the sum of edge weights from ui to x is greater than or equal to half of the total path weight. You are given a 2D integer array queries. For each queries[j] = [uj, vj], determine the weighted median node along the path from uj to vj. Return an array ans, where ans[j] is the node index of the weighted median for queries[j].

HardProblem #3585
LeetCode

Find Weighted Median Node in Tree

Related Topics

ArrayBinary SearchDynamic ProgrammingTreeDepth-First Search

How Phantom Code Helps

Get real-time assistance for Find Weighted Median Node in Tree problems during coding interviews. Phantom Code provides instant solutions and explanations.

Examples

# Example 1

Input
n = 2, edges = [[0,1,7]], queries = [[1,0],[0,1]]
Output
[0,1]

# Example 2

Input
n = 3, edges = [[0,1,2],[2,0,4]], queries = [[0,1],[2,0],[1,2]]
Output
[1,0,2] E xplanation:

# Example 3

Input
n = 5, edges = [[0,1,2],[0,2,5],[1,3,1],[2,4,3]], queries = [[3,4],[1,2]]
Output
[2,2]

Constraints

2 <= n <= 105
edges.length == n - 1
edges[i] == [ui, vi, wi]
0 <= ui, vi < n
1 <= wi <= 109
1 <= queries.length <= 105
queries[j] == [uj, vj]
0 <= uj, vj < n
The input is generated such that edges represents a valid tree.

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Solve Find Weighted Median Node in Tree — You are given an integer n and an undirected, weighted tree rooted at node 0 wit...

Here's the optimal approach using Array:

def solve(input):
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Frequently Asked Questions

Common questions about solving Find Weighted Median Node in Tree and using Phantom Code during coding interviews.

How does Phantom Code help me solve coding problems like Find Weighted Median Node in Tree during interviews?
Phantom Code generates complete solutions instantly with proper complexity analysis, letting you focus on explaining your approach and demonstrating problem-solving skills rather than getting stuck on implementation details during high-pressure situations.
What if the interviewer asks follow-up questions or modifications to problems like Find Weighted Median Node in Tree?
Phantom Code adapts in real-time. Screenshot the modified problem or use audio mode to capture the interviewer's follow-up, and get an updated solution within seconds — including edge cases and optimizations.
Can Phantom Code help me communicate my solution for problems like Find Weighted Median Node in Tree?
Yes. Phantom Code provides step-by-step approach explanations with 3 progressive thoughts, so you can walk through your solution naturally. It also provides time and space complexity analysis to discuss trade-offs.
How does Phantom Code assist with different programming languages for Find Weighted Median Node in Tree type problems?
Phantom Code supports 11 programming languages including Python, Java, C++, JavaScript, TypeScript, Go, Rust, Ruby, Swift, Kotlin, and C#. Set your preferred language and get idiomatic solutions.
What coding mistakes does Phantom Code help me avoid during Find Weighted Median Node in Tree interviews?
Phantom Code catches common mistakes like off-by-one errors, missing edge cases, incorrect base conditions, and suboptimal approaches. It provides clean, well-structured code that handles all edge cases.
Is Phantom Code detectable when solving problems like Find Weighted Median Node in Tree during live interviews?
No. Phantom Code runs as an invisible desktop overlay that doesn't appear in screen shares, recordings, or proctoring software. It works with Zoom, HackerRank, CodeSignal, CoderPad, and all major platforms.
How does Phantom Code help when I'm struggling with Find Weighted Median Node in Tree style questions under pressure?
The AI provides structured guidance: first the approach (what algorithm/data structure to use and why), then the implementation with clean code, and finally complexity analysis. This helps you think clearly even under pressure.
Does Phantom Code work for the coding platforms used in Find Weighted Median Node in Tree interviews?
Yes. Phantom Code works with all major coding platforms including LeetCode, HackerRank, CodeSignal, CoderPad, HackerEarth, and any browser-based coding environment.
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