问题描述
我有一个R的聚类图，而我想用wss图来优化聚类的肘标准，所以我为我的聚类画了一个wss图，但看起来确实很奇怪，我不知道有多少个弯头我应该聚类，有人可以帮助我吗？
I have a cluster plot by R while I want to optimize the "elbow criterion" of clustering with a wss plot, so I drew a wss plot for my cluster, but is looks really strange and I do not know how many elbows should I cluster, anyone could help me?
这是我的数据：
Here is my data:
Friendly<-c(0.533,0.854,0.9585,0.925,0.9125,0.9815,0.9645,0.981,0.9935,0.9585,0.996,0.956,0.9415)
Polite<-c(0,0.45,0.977,0.9915,0.929,0.981,0.9895,0.9875,1,0.96,0.996,0.873,0.9125)
Praising<-c(0,0,0.437,0.9585,0.9415,0.9605,0.998,0.998,0.8915,1,1,1,0.977)
Joking<-c(0,0,0,0.617,0.942,0.9665,0.9935,0.992,0.935,0.987,0.975,0.9915,0.9665)
Sincere<-c(0,0,0,0,0.617,0.8335,0.985,0.9895,0.977,0.9205,1,0.9585,0.8895)
Serious<-c(0,0,0,0,1,0.642,0.975,0.9605,0.9645,0.9895,0.8125,0.9605,0.925)
Hostile<-c(0,0,0,0,0,0,0.629,0.656,0.948,0.9705,0.9645,0.998,0.9685)
Rude<-c(0,0,0,0,0,0,0,0.687,0.979,0.954,0.954,0.996,0.956)
Irony<-c(0,0,0,0,0,0,0,0,0.354,0.9815,0.996,1,0.971)
Insincere<-c(0,0,0,0,0,0,0,0,1,0.396,0.996,0.9915,0.9415)
Commanding<-c(0,0,0,0,0,0,0,0,0,1,0.462,0.9605,0.9165)
Suggesting<-c(0,0,0,0,0,0,0,0,0,0,0,0.867,0.775)
Neutral<-c(0,0,0,0,0,0,0,0,0,0,0,0,0.283)
data <- data.frame(Friendly,Polite,Praising,Joking,Sincere,Serious,Hostile,Rude,Blaming,Insincere,Commanding,Suggesting,Neutral)
这是我的聚类代码：加文（Gavin）在以下方法的最后一行中给出了此方法：
And here is my code of clustering: the method is given by Gavin in the last line of :How to draw the plot of within-cluster sum-of-squares for a cluster?
##cluster analysis
dist<-as.dist(data)
hc<-hclust(dist, method="average")
plot(hc, main="", sub='Method="Average"', ann=T, axes=T, hang=0.2)
##draw a wss plot
res <- sapply(seq.int(1, 13), wrap, h = hc, x = data)
plot(seq_along(res), res, type="b", pch=19)
但是看起来像这样，任何人都可以解释为什么会发生这种情况以及如何确定肘部标准？
But it looks like this, anyone can explain why this happened and how to decide the "elbow criterion"?
推荐答案
您为什么期望WSS随着群集数量的增加而平稳下降？正如您所发现的，它不需要。仅凭表现良好的数据，我才能看到表现良好的卵石图。
Why do you expect that WSS will decline smoothly with increasing numbers of clusters? It need not, as you found out. Only with well-behaved data have I seen nicely behaved scree plots.
WSS有7个群集，下降幅度很大，这可能表明您想停在那里。但是，在评估时，您还应该查看树状图。
There is a big drop in the WSS with 7 clusters which might suggest you want to stop there. However, you should also look at the dendrogram when you evaluate this.
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