我已经confusionMatrix()
使用以下代码为多个电台进行了计算
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来计算基于不同混淆矩阵的索引
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")
预先感谢您提供的任何帮助!
as.matrix()
在此示例中使用该功能的问题是您正在创建列表列表。代替:
as.matrix(result, what = "classes")
as.matrix(result, what = "overall")
尝试创建数据框来容纳您的结果,您可以通过遍历原始result
列表来填充结果。下面的代码应该可以解决问题。
## iterate through all six parts of the confusionMatrix: "positive", "table", "overall", "byClass", "mode", "dots"
for(i in 1:length(names(result[[1]]))){
##create a data frame to house the data for export
data <- data.frame()
## iterate through all results; in the example we have Aizawl" and "Serchhip"
for(j in 1:length(names(result))){
## load the data into a data frame
df <- data.frame(result[[j]][i])
## if data is empty no need to alter or append to data frame so skip to next
if(nrow(df)==0){next}
## add a name column for identifying between result sets; in the example we have Aizawl" and "Serchhip"
df$name <- names(result)[j]
## append the loaded data to the data frame for export
data <- rbind(data, df)
}
## if data is empty no need to export, therefore skip to next
if(nrow(data)==0){next}
## write the data to a csv with the name of the part of the condusionMatrix it contains
## row.names changed to TRUE based on OP's comments
write.csv(data, file = paste0(names(result[[1]])[i],".csv"), row.names = TRUE, na = "")
}
除非,否则您希望可以在使用该write.csv()
函数之前转换数据帧。在这种情况下,您可以使用
for(i in 1:length(names(result[[1]]))){
data <- data.frame()
for(j in 1:length(names(result))){
df <- data.frame(result[[j]][i])
if(nrow(df)==0){next}
df$name <- names(result)[j]
data <- rbind(data, df)
}
if(nrow(data)==0){next}
assign(names(result[[1]])[i], data)
}
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