Hi all ,
I was doing k-mean clustering through which i
could find out each and every clusters and the contents
around each cluster centroid like below :-
x<-read.csv("normalizedata.csv", header = TRUE) #To read the dataset
km<- kmeans(x, 3, 150)
print(km) <<<---- in this I could get every clusters and
centroids .
km$cluster <<----- It gave me the clusters which comes
up during clustering like
[1] 3 3 1 2 3 2 1 2 1 3 2 1 3 1 1 1 3 2 1 1 1 1 3 1 1 2 2 2 1 3 3 1 3 3 2
2 2
[38] 3 1 3 1 3 3 1 1 1 3 1 1 2 1 3 3 3 3 3 3 3 3 3 3 1 3 2 3 2 2 3 3 3 3 2
3 2
[75] 1 2 2 1 1 3 3 1 3 1 1 1 1 3 3 2 1 3 3 3 1 3 1 1 1 1 1 2 1 3 1 1 1 2 1
3 3
[112] 1 3 1 2 1 1 1 1 1 1 1 2 2 1 3 1 2 3 1 1 3 2 1 1 1 2 1 3 2 1 3 1 1 1 3
2 1
[149] 3 2 3 3 3 3 1 2 1 1 1 1 1 1 3 2 2 2 1 1 1 3 3 1 1 3 2 1 3 1 1 1 1 1 2
1 1
[186] 3 1 2 1 3 2 3 2 1 2 1 2 3 1 1 1 2 3 2 1 1 2 3 3 1 2 2 1 3 1 1 2 3 3 1
1 3
[223] 3 1 1 3 3 3 2 2 1 3 3 3 2 2 1 2 3 1 1 2 1 1 1 1 1 3 1 3 2 1 1 3 1 1 2
2 3
[260] 1 3 3 3 1 1 2 1 3 1 3 1 2 1 1 1 3 3 2 3 1 1 1 2 1 3 3 1 3 3 1 1 2 1 2
3 3
But in case of SOM clustering when i had tried like :-
require(kohonen)
require (som) #To load Kohonen Package
x<-read.csv("normalizedata.csv",header=TRUE)
x.sc <- scale(x) #To scale
set.seed(7)
xx.som<- SOM(data = x.sc, grid = somgrid(1, 3, "hexagonal")) #som
function
print(xx.som)
I got :-
$codes
hrefCount Number.of.times.Visited Total.time.Spent
[1,] -0.008926424 0.01642686 -0.01059301
[2,] -0.008926424 0.01642686 -0.01059301
[3,] -0.023231402 -0.06730921 -0.02705149
I hope this are the centroids , I need the cluster results
like kmeans , how to achieve it , can any one helps .
THanks
ASHIS
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