Question

我有以下列表，我正在尝试创建类似于以下的内容（不是ROC曲线，只是标准偏差部分）;

图片来自以下链接（用Python编写）link

结构：

List of 2
 $ newcol    :List of 6
  ..$ : num [1:75] 0.887 0.903 0.909 0.912 0.914 ...
  ..$ : num [1:75] 0.921 0.939 0.947 0.951 0.954 ...
  ..$ : num [1:75] 0.887 0.906 0.912 0.915 0.917 ...
  ..$ : num [1:75] 0.917 0.939 0.947 0.951 0.954 ...
  ..$ : num [1:75] 0.889 0.907 0.913 0.917 0.92 ...
  ..$ : num [1:75] 0.921 0.942 0.95 0.954 0.957 ...
 $ newcol_std:List of 6
  ..$ : num [1:75] 0.00409 0.00273 0.00269 0.00343 0.00229 ...
  ..$ : num [1:75] 0.002934 0.002618 0.001522 0.001453 0.000926 ...
  ..$ : num [1:75] 0.00357 0.00153 0.00151 0.00134 0.0012 ...
  ..$ : num [1:75] 0.003542 0.002235 0.000998 0.000965 0.000733 ...
  ..$ : num [1:75] 0.0037 0.002689 0.001815 0.001497 0.000975 ...
  ..$ : num [1:75] 0.0024 0.0015 0.00145 0.00147 0.00135 ...

数据：

structure(list(newcol = list(c(0.8872707, 0.9030507, 0.9087002, 
0.9121047, 0.9138395, 0.9152718, 0.9158744, 0.9171358, 0.9177393, 
0.9183246, 0.9187044, 0.9189548, 0.9193481, 0.9197915, 0.9200788, 
0.9204141, 0.9205686, 0.9207148, 0.9211112, 0.9212452, 0.9214546, 
0.9216964, 0.9218029, 0.9219894, 0.9221818, 0.9223518, 0.9224333, 
0.9227003, 0.9228383, 0.923039, 0.9231552, 0.9233157, 0.9235961, 
0.9238084, 0.9239563, 0.9241449, 0.9242382, 0.9243814, 0.9245184, 
0.9246821, 0.9248516, 0.9249441, 0.9250369, 0.9251405, 0.9253599, 
0.9255014, 0.9256391, 0.9257434, 0.9258243, 0.925896, 0.9259839, 
0.9261379, 0.9262587, 0.9263849, 0.9265621, 0.9266335, 0.9268006, 
0.9268646, 0.9269769, 0.9271026, 0.927221, 0.9273457, 0.9274789, 
0.9276086, 0.9276941, 0.9278218, 0.9279294, 0.928021, 0.9281182, 
0.9282149, 0.9283187, 0.928444, 0.9285454, 0.9286198, 0.9287347
), c(0.9206486, 0.9394105, 0.9466493, 0.9507703, 0.9537551, 0.9552856, 
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0.000182688505453927, 0.000174160873949313, 0.00018797340223593, 
0.000246924361030111, 0.000294463257588724, 0.000306835200015461, 
0.000305214498530033, 0.000337968045965656, 0.000337387255025373, 
0.000342226606233019, 0.000323973903402572, 0.000322282004089188, 
0.000292371612916264, 0.000269445820269462, 0.000248882220955965, 
0.000237522230775312, 0.000236329769355559, 0.000216712805608366, 
0.0002249330790598, 0.000233720687792251))), .Names = c("newcol", 
"newcol_std"))

编辑：

我有以下情节，我试图绘制标准偏差（类似于第一张图片）。

图表是来自CV的每个nround之后的AUC分数。所以基本上，在nrounds

中xgb.cv的数量之后，模型的改善程度会降低

图表不是@missuse指出的ROC图表。

Answer 1

这是一种方法：

library(tidyverse)

do.call(cbind, df$newcol) %>% #convert the first list element to a data frame
  as.data.frame %>%
  mutate(n = 1:n()) %>% #label observations 
  gather(key, value, 1:6) %>% #convert to long format
  bind_cols(do.call(cbind, df$newcol_std) %>% #convert the second list element to a data frame
                 as.data.frame %>%
                 gather(key, value)%>% #convert to long format
              select(-key)) %>% #drop unneeded column
  ggplot()+
    geom_line(aes(x = n, y = value, color = key))+
    geom_ribbon(aes(x = n, ymin = value-value1, ymax = value+value1, fill = key), alpha = 0.4)

在ggplot中绘制两个列表

1 个答案: