# Interpret the visualization of k-mean clusters

Following my posted data here, I conducted a k-mean clustering analysis. I refereed to this post: How to produce a pretty plot of the results of k-means cluster analysis? for the clusters visualization

# Read and Sort Input Data
mydata2 <- scale(mydata)  # Normalize the data

# Determine number of clusters
wssplot(mydata2)
set.seed(1234)
nc <- NbClust(mydata2, min.nc=2, max.nc=15, method="kmeans")
table(nc$Best.n[1,]) # Do K-means clustering set.seed(1234) fit.km <- kmeans(mydata2, centers = 3, nstart=25) # Visualize the clusters # Fig 1 plotcluster(mydata2, fit.km$cluster)
# Fig 2
clusplot(mydata2, fit.km$cluster, color=TRUE, shade=TRUE,labels=2, lines=0) # Fig 3 with(mydata, pairs(mydata2, col=c(1:3)[fit.km$cluster]))


The NbClust indicates 2 clusters:

Here are the visualization of clusters:

I am not sure how to interpret the clusters visualization result. 1) The 1st cluster plot is doing "Centroid Plot against 1st 2 discriminant functions". It seemed the clusters showed three groups. 2) The 2nd cluster plot "vary parameters for most readable graph" (referred from Quick-R: Cluster Analysis).