使用R中的管道运算符应用confusionMatrix

问题描述 投票：0回答：1

我想使用管道运算符将confusionMatrix应用于xtabs对象。我使用了以下代码

library(tidyverse)
df %>% 
  xtabs( ~ Observed + Forecasted + Station, data =.) %>% 
  caret::confusionMatrix(.)

这给我以下错误

confusionMatrix.table（。）中的错误：表必须具有两个维

我可以将其应用于单个电台，例如

df %>% subset(Station == "Aizawl") %>% 
  xtabs( ~ Observed + Forecasted, data =.) %>% 
  caret::confusionMatrix(.)

现在如何一次计算所有电台的confusionMatrix？

数据

df = structure(list(Station = c("Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", "Aizawl", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", 
"Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip", "Serchhip"
), Observed = c(1, 1, 1, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 
1, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 3, 3, 4, 1, 1, 4, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
4, 4, 4, 3, 4, 1, 1, 1, 1, 1, 3, 5, 5, 5, 3, 1, 1, 3, 1, 1, 1, 
1, 1, 5, 3, 4, 1, 1, 1, 1, 1, 3, 1, 4, 1, 1, 1, 1, 1, 4, 4, 5, 
1, 5, 4, 5, 5, 5, 5, 1, 5, 1, 4, 5, 4, 4, 5, 4, 5, 5, 3, 1, 5, 
3, 4, 3, 4, 5, 5, 5, 5, 4, 4, 5, 4, 4, 5, 5, 5, 5, 4, 5, 5, 5, 
5, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 3, 5, 5, 1, 1, 3, 4, 1, 1, 1, 1, 1, 1, 1, 1, 
3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 3, 
3, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 1, 3, 4, 1, 1, 1, 1, 1, 1, 1, 
1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 
6, 5, 5, 4, 1, 5, 1, 1, 1, 1, 4, 5, 5, 5, 5, 5, 5, 1, 1, 4, 1, 
4, 4, 4, 5, 1, 1, 4, 3, 5, 4, 5, 5, 5, 5, 5, 4, 4, 4, 4, 5, 1, 
6, 5, 5), Forecasted = c(1, 1, 1, 5, 5, 1, 1, 1, 5, 5, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 5, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 4, 4, 1, 1, 5, 3, 1, 
1, 1, 4, 5, 5, 5, 5, 1, 1, 1, 5, 5, 1, 5, 5, 5, 4, 5, 4, 4, 4, 
3, 4, 4, 1, 1, 5, 5, 4, 4, 4, 1, 1, 1, 4, 4, 4, 4, 4, 4, 1, 1, 
5, 4, 4, 5, 4, 4, 4, 4, 5, 4, 5, 5, 5, 5, 5, 4, 5, 5, 4, 1, 1, 
4, 4, 5, 5, 5, 5, 1, 4, 5, 5, 1, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 5, 1, 1, 1, 5, 4, 1, 1, 1, 5, 4, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 5, 5, 5, 6, 5, 5, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 5, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 5, 5, 4, 1, 1, 1, 1, 1, 4, 1, 1, 1, 4, 4, 4, 4, 1, 4, 1, 3, 
1, 1, 1, 4, 4, 4, 4, 4, 4, 1, 1, 1, 4, 4, 3, 5, 5, 5, 4, 3, 5, 
5, 5, 5, 5, 4, 5, 5, 5, 4, 5, 4, 4, 5, 5, 4, 4, 5, 4, 1, 4, 4, 
5, 5, 4, 5, 4, 5, 4, 5, 5, 5, 1, 4, 5, 5, 5, 4, 5, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 6)), row.names = c(NA, 333L), class = "data.frame")
r tidyverse r-caret confusion-matrix
1个回答
1
投票

如果在整个data.frame上执行此操作，则会得到由工作站分隔的表数组，因此confusionMatrix（）抱怨：

xtabs( ~ Observed + Forecasted + Station, data =df)
, , Station = Aizawl

        Forecasted
Observed  1  3  4  5  6
       1 56  2 13 13  0
       3 12  0  4  8  0
       4  4  0  9 11  0
       5  3  0  7 23  0
       6  0  0  0  0  0

, , Station = Serchhip

        Forecasted
Observed  1  3  4  5  6
       1 76  3 18 18  0
       3  4  0  2  5  0
       4  2  0  4 12  0
       5  1  0  9 10  2
       6  0  0  0  2  0

因此，您可以尝试将array_tree()与margin = 3一起使用，以将其转换为列表，可以使用map（）来应用混淆矩阵：

df %>% 
xtabs( ~ Observed + Forecasted + Station, data =.) %>% 
array_tree(.,margin=3) %>% 
map(~caret::confusionMatrix(as.table(.x)))
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