如何在 R 中总结 pam 聚类结果？

Question

如果我尝试运行下面的代码来获取我的聚类结果的摘要，我会收到以下错误：

Error in UseMethod("mutate_") : no applicable method for 'mutate_' applied to an object of class "table"

如果 dat_ 是数据框，则此代码有效，但如果是表，则会收到上述错误消息。有没有人有办法解决吗？

    pam_fit <- pam(gower_dist, diss = TRUE, k)  # performs cluster analysis
    pam_results <- dat %>%
      mutate(cluster = pam_fit$clustering) %>%
      group_by(cluster) %>%
      do(the_summary = summary(.))
    pam_results$the_summary

样本数据集：

set.seed(1)
dat <- data.frame(ID = rep(sample(c("a","b","c","d","e","f","g"),10,replace = TRUE),70),
                 disease = sample(c("flu","headache","pain","inflammation","depression","infection","chest pain"),100,replace = TRUE))

dat <- unique(dat)

dat2 <- table(dat)
dat3 <- as.data.frame(dat)

Answer 1

如果您查看 dat，每个 ID 都有多个观察值，并且您正在尝试根据其疾病列将 ID 划分为集群。所以你的集群结果应该和你的id一样长，如果你想总结你的结果，你就按集群来。

要将表格放在一起，请执行以下操作：

library(cluster)
library(tidyverse)

pam_fit <- pam(daisy(dat2,"gower"), diss = TRUE, 2)  # performs cluster analysis

pam_results <- as.data.frame.matrix(table(dat)) %>%
mutate(cluster = pam_fit$clustering) %>%
group_by(cluster) %>%
do(the_summary = summary(.),freq = colSums(.))

这给出了总结：

pam_results$freq
[[1]]
  chest pain   depression          flu     headache    infection inflammation 
           4            5            4            3            5            3 
        pain      cluster 
           5            5 

[[2]]
  chest pain   depression          flu     headache    infection inflammation 
           1            2            2            2            2            2 
        pain      cluster 
           0            4 

如果你只需要频率，你可以这样做：

aggregate(as.data.frame.matrix(dat2[,-1]),list(cluster=pam_fit$clustering),sum)
      cluster depression flu headache infection inflammation pain
    1       1          5   4        3         5            3    5
    2       2          2   2        2         2            2    0

或 dplyr 解决方案：

as.data.frame.matrix(dat2[,-1]) %>% 
mutate(cluster=pam_fit$clustering) %>%
group_by(cluster) %>%
summarize_all(sum)

# A tibble: 2 x 7
  cluster depression   flu headache infection inflammation  pain
    <int>      <int> <int>    <int>     <int>        <int> <int>
1       1          5     4        3         5            3     5
2       2          2     2        2         2            2     0