Database Reference
In-Depth Information
2 2 2 2 3 3 2 2 2 2
[401] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2
2 2 2 2 2 2 2 2 2 2
[441] 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2
2 2 3
2 2 2 2 2 2 2 2 3 2
[481] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2
2 2 2 2 2 2 2 2 2 2
[521] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2
2 2 2 2 2 2 2 2 2 2
[561] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2
2 2 2 2 2 2 2 2 2 2
[601] 3 3 2 2 3 3 3 3 1 1 3 3 3 2 2 3 2 3 3 3
Within cluster sum of squares by cluster:
[1] 6692.589 34806.339 22984.131
(between_SS / total_SS = 76.5 %)
Available components:
[1] "cluster" "centers" "totss" "withinss" "tot.withinss"
[6] "betweenss" "size" "iter" "ifault"
The displayed contents of the variable
km
include the following:
• The location of the cluster means
• A clustering vector that defines the membership of each student to a
corresponding cluster 1, 2, or 3
• The WSS of each cluster
• A list of all the available k-means components
The reader can find details on these components and using k-means in R by
employing the help facility.
The reader may have wondered whether the k-means results stored in
km
are
equivalent to the WSS results obtained earlier in generating the plot in
Figure 4.5
.
The following check verifies that the results are indeed equivalent.
