如何解决这个聚类分析？

Question

我正在计算最佳簇数。我用了NbClust函数来计算，但是怎么显示缺失值太多但是我不知道，我的数据中没有缺失值。

表明 “NbClust 中的错误（数据 = df，距离 = “euclidean”，min.nc = 2，max.nc = 20，： TSS 矩阵是不确定的。一定是缺失值太多了。无法计算索引。"

我正在使用的数据

dput(read.csv("cluster.csv"))
df = structure(list(St = c("PE", "SU", "PA", "OC", "PE", 
"AC", "PP", "RA"), NDDZ91 = c(0.253576604, 0.0551232, 
-0.53169303, -0.533246481, -0.533634844, -0.529751216, -0.529751216, 
2.349376982), NDDZ92 = c(0.4633855, 0.952926247, -0.905688982, 
-0.908031282, 0.815565566, -0.904127448, -0.904127448, 1.390097848
), NDDZ94 = c(0.971257769, 0.602251213, -0.82539626, -0.831562179, 
0.018490857, -0.826819164, -0.826819164, 1.718596929), NDDZ95 = c(2.428086592, 
-0.050766856, -0.502772844, -0.503557157, -0.289546405, -0.502953839, 
-0.502953839, -0.075535652), NDDZ96 = c(0.073650972, 0.482511184, 
-0.669130113, -0.675742407, -0.675742407, -0.664721917, -0.09563249, 
2.224807178), NDDZ97 = c(2.108725851, 0.193018074, -0.616096838, 
-0.618190279, 0.782927149, -0.616096838, -0.616096838, -0.618190279
), NDDZ98 = c(0.422792635, 0.224274925, -0.66324044, -0.674453783, 
-0.191577267, -0.670300693, -0.670300693, 2.222805316), NDDZ99 = c(-0.045504148, 
0.621635607, -1.030110408, -1.033331082, 0.370677267, 0.370677267, 
-1.028730119, 1.774685616), NDDZ103 = c(0.543822029, 1.4294128, 
-0.862935822, -0.865183039, 0.206064797, -0.865183039, -0.863310358, 
1.277312632), NDDZ105 = c(-0.242116717, -0.327002284, -0.599905416, 
-0.602682046, 0.790140631, -0.602682046, -0.598715431, 2.18296331
), NDDZ106 = c(-0.394116657, 1.166937427, -1.070650174, -1.078708713, 
0.81841561, -1.078708713, 0.81841561, 0.81841561), NDDZ107 = c(1.493844177, 
0.766047601, -1.041282102, -1.04295136, 0.956552995, -0.043914579, 
-1.044382153, -0.043914579), NDDZ112 = c(2.137032432, 0.085031825, 
-0.601376567, -0.601897927, -0.601897927, -0.601153126, 0.785414418, 
-0.601153126), NDDZ113 = c(-0.102481763, -0.288855624, -0.41345193, 
-0.41414606, -0.414377436, -0.413220553, 2.45975392, -0.413220553
), NDDZ114 = c(0.100876842, 0.716344963, -0.756031568, -0.758896113, 
0.173403417, -0.756850009, -0.756850009, 2.038002477), NDDZ115 = c(-0.058558995, 
0.221455542, -0.509307832, -0.505965142, -0.510336352, -0.507765052, 
-0.507765052, 2.378242882), NDDZ116 = c(1.377841856, 1.640112838, 
-0.676090962, -0.676661736, -0.676947124, -0.67409325, -0.67409325, 
0.359931628), NDDZ117 = c(2.177231217, 0.849368214, -0.539426784, 
-0.539639833, -0.479549446, -0.53892967, -0.509594639, -0.41945906
), NDDZ119 = c(2.215308855, 0.141088501, -0.679450372, -0.680029439, 
-0.106916185, -0.678099214, -0.678099214, 0.466197068), NDDZ122 = c(1.743810041, 
0.768581504, -0.772598602, -0.773098804, -0.348192016, -0.772598602, 
-0.772598602, 0.926695082), NDDZ123 = c(0.634144889, 1.11554263, 
-0.833927192, -0.834643558, -0.021473135, -0.832255672, -0.832255672, 
1.60486771)), class = "data.frame", row.names = c(NA, -8L))

到目前为止我已经完成的代码工作

rownames(df) = c(df$St)
df = df[,-1]
library(NbClust)
nbclust_out <- NbClust(
  data = df,
  distance = "euclidean",
  min.nc = 2,
  max.nc = 20,
  method = "ward.D",
)

但是这个错误显示如下“NbClust 中的错误（data = df，distance = “euclidean”，min.nc = 2，max.nc = 20，： TSS 矩阵是不确定的。一定是缺失值太多了。无法计算索引。"

Answer 1

max.nc 高于数据集中的行，这可能会导致您的问题。使用其他包：

#remove factor column
df$St <- NULL

#scale df
df.scaled <- scale(df)

#scree plot
scree <- fviz_nbclust(df.scaled, FUNcluster = kmeans, method = "wss", k.max = 7)

#parallel analysis
paral <- fa.parallel(df.scaled, fa = "pc")

根据下面的图，我建议使用 3 个集群。但是并行分析给出的错误是你的数据集中有超海伍德案例，要仔细检查你的结果。

如何解决这个聚类分析？

How to solve this cluster analysis?

r

cluster-computing

hierarchical-clustering