GNU/Linux Desktop Survival Guide
by Graham Williams
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GNU/Linux Desktop Survival Guide by Graham Williams |
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The task is to read some data, extract some numeric fields, convert to a matrix for efficiency (rather than data frame), and cluster.
df <- read.csv("wine.csv") # Read in some data.
ds <- as.matrix(df[,1:10]) # Extract numeric into matrix.
cl <- kmeans(ds, 10) # Generate 10 clusters.
plot(ds, col=cl$cluster) # Show the clusters.
plot(ds[,c(12,13)], col=cl$cluster) # Show just two variable plot.
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The resulting cluster will have the following fields:
| $cluster: | The cluster that each row belongs to. |
| $centers: | The medoid of each cluster. |
| $withinss: | The within cluster sum of squares. |
| $size: | The size of each cluster. |
