What is minimum spanning tree explain Kruskal and Prim algorithm?

Difference between Prim’s and Kruskal’s algorithm for MST

Can Prims and Kruskal algorithm give different minimum spanning trees?

In general: If the edge weights in your graph are all different from each other, then your graph has a unique minimum spanning tree, so Kruskal’s and Prim’s algorithms are guaranteed to return the same tree.

What is minimum spanning tree explain Kruskal algorithm with the help of an example?

Kruskal’s algorithm to find the minimum cost spanning tree uses the greedy approach. This algorithm treats the graph as a forest and every node it has as an individual tree. A tree connects to another only and only if, it has the least cost among all available options and does not violate MST properties.

Will both Prims and Kruskal give same results?

For there to be the possibility of multiple MSTs, at least two edges in the graph must be equal. Therefore, the MST is unique, and both Prim’s and Kruskal’s algorithm will return the same result.

Which one is better Prims or Kruskal?

Prim’s algorithm is significantly faster in the limit when you’ve got a really dense graph with many more edges than vertices. Kruskal performs better in typical situations (sparse graphs) because it uses simpler data structures.

What is the purpose of minimum spanning tree?

A minimum spanning tree is a special kind of tree that minimizes the lengths (or “weights”) of the edges of the tree. An example is a cable company wanting to lay line to multiple neighborhoods; by minimizing the amount of cable laid, the cable company will save money.

What is a minimum spanning tree explain Kruskal’s algorithm for finding a minimum spanning tree?

It is a Greedy Algorithm. The Greedy Choice is to put the smallest weight edge that does not because a cycle in the MST constructed so far. If the graph is not linked, then it finds a Minimum Spanning Tree.