Cluster vector get a zero one matrix in R

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Let's say I have a cluster vector generated by any clustering method, like the following on the iris data:

data(iris)
kmeans_res <- kmeans(x = iris[,c(1:4)], centers = 3)
kmeans_res$cluster

Is there an efficient way to create a matrix with zeros and ones based on this vector?

The rows and the columns of this matrix are the observations from the dataset from 1 to n. And the entries should be one, if e.g. observations 5 and 8 belong to the same cluster and zero otherwise.

The problem could be solved with a loop, but this doesn't seem very elegant. Can you think of another solution?

cluster-analysis vector r matrix
1 Answers

You may use outer.

M <- +(outer(v, v, `==`))
M[50:60, 50:60]
#       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#  [1,]    1    0    0    0    0    0    0    0    0     0     0
#  [2,]    0    1    1    0    1    1    1    1    1     1     1
#  [3,]    0    1    1    0    1    1    1    1    1     1     1
#  [4,]    0    0    0    1    0    0    0    0    0     0     0
#  [5,]    0    1    1    0    1    1    1    1    1     1     1
#  [6,]    0    1    1    0    1    1    1    1    1     1     1
#  [7,]    0    1    1    0    1    1    1    1    1     1     1
#  [8,]    0    1    1    0    1    1    1    1    1     1     1
#  [9,]    0    1    1    0    1    1    1    1    1     1     1
# [10,]    0    1    1    0    1    1    1    1    1     1     1
# [11,]    0    1    1    0    1    1    1    1    1     1     1

v[50:60]
# [1] 1 2 2 3 2 2 2 2 2 2 2

Data:

v <- kmeans_res$cluster
user_65740380
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