问题
In below kmeans analysis I am assigning a 1 or 0 to indicate if word is associated with a user :
cells = c(1,1,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,0,1,1,1,1,1,1)
rnames = c("a1","a2","a3","a4","a5","a6","a7","a8","a9")
cnames = c("google","so","test")
x <- matrix(cells, nrow=9, ncol=3, byrow=TRUE, dimnames=list(rnames, cnames))
# run K-Means
km <- kmeans(x, 3, 15)
# print components of km
print(km)
# plot clusters
plot(x, col = km$cluster)
# plot centers
points(km$centers, col = 1:2, pch = 8)
This is the graph :
Why do I not receive multiple points around each cluster ? What is this graph indicating. I would like to suggest a word to a user depending on if another use has the same word configured.
回答1:
You don't see multiple points because your data are discrete, categorical observations. K-means is really only suitable for grouping continuous observations. Your data can only appear on three points on the plot you've shown and three points don't make a nice "cloud" of data.
This suggests to me that k-means is probably not appropriate for your specific problem.
Incidentally, when I run the code above, I get the plot below, which is different from the one you've shown us. Perhaps this is more like what you are expecting? The green green data point belongs to (is "around") the upper-right cluster centre indicated by a black asterisk.
来源：https://stackoverflow.com/questions/17450486/why-am-i-not-getting-points-around-clusers-in-this-kmeans-implementation