【发布时间】:2020-09-19 15:12:26
【问题描述】:
我使用以下代码为多个站点计算了confusionMatrix()
library(tidyverse)
result <- df %>%
xtabs( ~ Observed + Forecasted + Station, data =.) %>%
array_tree(.,margin=3) %>%
map(~caret::confusionMatrix(as.table(.x)))
然后我尝试使用以下代码计算不同的基于混淆矩阵的索引
as.matrix(result, what = "classes")
as.matrix(result, what = "overall")
返回:
#> [,1]
#> Aizawl List,6
#> Serchhip List,6
我的问题是如何将输出写入.csv 文件?
以下是一些示例数据来帮助说明我的问题:
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")
提前感谢您提供的任何帮助!
【问题讨论】:
标签: r tidyverse r-caret confusion-matrix