valesdn said:Hi guys.
Could you please give me more information regarding the necessary library and/or the code I should use to compute the Minimum Spanning Tree in R?
Many thanks.
valesdn said:Actually it is not a homework question. I read an article regarding analysis data and MST, so I tried to 'copy' a part of the program on a new file in R. However, I found some difficult to create the algorithm of this function in R.
I usually used this program for financial data analysis, but in a really easy way.
A minimum spanning tree is a subset of edges of a connected, undirected graph that connects all the vertices together with the minimum possible total edge weight. In other words, it is a tree that connects all the vertices with the minimum total cost.
MST is important in data analysis because it helps identify the most efficient way to connect a network of data points. This can be useful in various applications such as minimizing costs in transportation or communication networks, identifying the most important features in a dataset, and reducing redundancy in data.
In R, MST can be calculated using the "mst" function in the "igraph" package. This function takes in a graph object as its input and returns a minimum spanning tree object with the minimum total edge weight.
Yes, MST can be used for both weighted and unweighted graphs. In weighted graphs, the edge weight represents the cost or distance between the vertices, while in unweighted graphs, all edges have the same weight and the minimum spanning tree is simply the tree with the minimum number of edges that connects all the vertices.
MST can be visualized in R using the "plot" function on the minimum spanning tree object. This will generate a plot of the MST, with the edge weights shown as labels on the edges. Alternatively, the "igraph" package also has various visualization functions that can be used to plot the MST.