compute.costs.proximity.graph {mstknnclust} | R Documentation |
Computes the edge costs sum of a proximity graph
Description
This function computes the edge costs (distances) overall sum of a proximity graph.
Usage
compute.costs.proximity.graph(graph.edges, distance.matrix)
Arguments
graph.edges |
A object of class "matrix" with two columns (object_i, object_j) representing the objects (nodes) of a proximity graph. |
distance.matrix |
A distance matrix between each pair of object i,j in the proximity graph. |
Value
total.costs.graph |
A numeric value representing the edge costs (distance) overall sum of a proximity graph. |
Examples
set.seed(1987)
##Generates a data matrix of dimension 50X13
n=50; m=13
x <- matrix(runif(n*m, min = -5, max = 10), nrow=n, ncol=m)
##Computes a distance matrix of x.
library("stats")
d <- base::as.matrix(stats::dist(x, method="euclidean"))
##Generates complete graph (CG)
cg <- generate.complete.graph(1:nrow(x),d)
##Generates a proximity graph (MST)
mstree <- generate.mst(cg)
##Calculate the edge cost sum of proximity graph (MST)
mstree.cost=as.numeric(compute.costs.proximity.graph(as.matrix(mstree$edges.mst.graph[,1:2]), d))
mstree.cost
##Generates a proximity graph (kNN)
knneig <- generate.knn(cg)
##Calculate the edge cost sum of proximity graph (kNN)
knneig.cost=as.numeric(compute.costs.proximity.graph(as.matrix(knneig$edges.knn.graph[,1:2]), d))
knneig.cost
[Package mstknnclust version 0.3.2 Index]