目测评估不同的 K 值

R 中的聚类分析

Dmitriy (Dima) Gorenshteyn

Lead Data Scientist, Memorial Sloan Kettering Cancer Center

簇内平方和总计：k = 1

簇内平方和总计：k = 2

簇内平方和总计：k = 3

簇内平方和总计：k = 4

肘部图

生成肘部图

model <- kmeans(x = lineup, centers = 2)
model$tot.withinss

[1] 1434.5

生成肘部图

library(purrr)

tot_withinss <- map_dbl(1:10,  function(k){
  model <- kmeans(x = lineup, centers = k)
  model$tot.withinss
})

elbow_df <- data.frame(
  k = 1:10,
  tot_withinss = tot_withinss
)
print(elbow_df)

    k tot_withinss
1   1    3489.9167
2   2    1434.5000
3   3     881.2500
4   4     637.2500
... ...   ...

生成肘部图

ggplot(elbow_df, aes(x = k, y = tot_withinss)) +
  geom_line() +
  scale_x_continuous(breaks = 1:10)

¡Vamos a practicar!

R 中的聚类分析