Stoer wagner min cut

[ArpitaHanjagi]

Algorithm: Stoer–Wagner Minimum Cut

Purpose: Finds the global minimum cut in an undirected weighted graph.

Theory: Repeatedly merges vertices while tracking the most tightly connected set, updating the minimum cut value.

Time Complexity: O(V³) for standard adjacency matrix implementation.

Space Complexity: O(V²) for adjacency matrix.

Input: Undirected weighted graph as an adjacency matrix or list.

Output: Minimum cut value and a representative vertex of the cut.

[Copilot]

Pull Request Overview

This pull request introduces a comprehensive implementation of the Stoer-Wagner minimum cut algorithm, along with substantial additions to graph algorithms, dynamic programming solutions, and machine learning implementations in R. The PR adds multiple new directories and files covering fundamental computer science algorithms and data structures.

Key Changes

• Implementation of 11+ graph algorithms including Stoer-Wagner min cut, Kruskal's MST, Prim's MST, and various path-finding algorithms
• Addition of 7+ dynamic programming solutions covering classic problems like knapsack, LCS, and subset sum
• Implementation of gradient boosting and bridge detection algorithms with comprehensive R6 class structures
• Creation of machine learning documentation and tutorial resources

Reviewed Changes

Copilot reviewed 138 out of 217 changed files in this pull request and generated 3 comments.

Show a summary per file

File	Description
graph_algorithms/stoer_wagner_min_cut.r	Core implementation of Stoer-Wagner algorithm for finding global minimum cut
graph_algorithms/kruskal_mst.r	Kruskal's MST with union-find data structure
graph_algorithms/prim_mst.r	Prim's algorithm for minimum spanning tree
graph_algorithms/dijkstra_shortest_path.r	Dijkstra's shortest path with priority queue
graph_algorithms/bellman_ford_shortest_path.r	Bellman-Ford algorithm supporting negative weights
graph_algorithms/floyd_warshall.r	All-pairs shortest path with R6 class structure
dynamic_programming/subset_sum.r	Subset sum problem with DP table visualization
dynamic_programming/longest_common_subsequence.r	LCS with multiple implementation variants
machine_learning/gradient_boosting.r	Complete gradient boosting implementation using R6
graph_algorithms/bridge_detector.r	Tarjan's bridge detection algorithm

[siriak]

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