Add Boruvka's MST in R#250
Closed
nachiket2005 wants to merge 3 commits into
Closed
Conversation
siriak
requested changes
Oct 24, 2025
| @@ -0,0 +1,26 @@ | |||
| # Boruvka's Minimum Spanning Tree (MST) | |||
|
|
|||
| This document describes the Boruvka MST implementation located at `R/graph_algorithms/boruvka_mst.r`. | |||
Member
There was a problem hiding this comment.
We don't add documentation separately from the code files, please remove it
|
This PR is stale because it has been open 30 days with no activity. Remove stale label or comment or this will be closed in 7 days. |
|
This PR was closed because it has been stalled for 7 days with no activity. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Overview
The
boruvka_mstfunction constructs a minimum spanning tree (MST) for an undirected weighted graph.It repeatedly adds the cheapest edge for each component, merging connected components until all vertices are included or no more edges can be added.
Key improvements over a naive implementation:
Graphs are represented as:
V: number of verticesedges: data frame with columnsu,v,wfor edges and weightsFeatures
Complexity