鉴于此data.frame:
library(dplyr)
library(stringr)
ml.mat2 <- structure(list(value = c("a", "b", "c"), ground_truth = c("label1, label3",
"label2", "label1"), predicted = c("label1", "label2,label3",
"label1")), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-3L))
glimpse(ml.mat2)
Observations: 3 Variables: 3 $ value <chr> "a", "b", "c" $ ground_truth <chr> "label1, label3", "label2", "label1" $ predicted <chr> "label1", "label2,label3", "label1"
我想在基于ground_truth
分割重复的标签之后测量每行的predicted
和,
之间的交叉长度。
换句话说,我希望长度为3的结果的值为2 2 1
。
我写了一个函数来做这个,但它似乎只在sapply
之外工作:
m_fn <- function(x,y) length(union(unlist(sapply(x, str_split,",")),
unlist(sapply(y, str_split,","))))
m_fn(ml.mat2$ground_truth[1], y = ml.mat2$predicted[1])
[1] 2
m_fn(ml.mat2$ground_truth[2], y = ml.mat2$predicted[2])
[1] 2
m_fn(ml.mat2$ground_truth[3], y = ml.mat2$predicted[3])
[1] 1
不是像这样或使用循环手动遍历数据集的行,我希望能够使用sapply
像这样对解决方案进行矢量化:
sapply(ml.mat2$ground_truth, m_fn, ml.mat2$predicted)
然而,意外的结果是:
label1, label3 label2 label1 4 3 3
由于您在相同的观察大小内进行迭代,因此您可以生成行数索引并在qazxsw poi中运行它:
sapply
或与sapply(1:nrow(ml.mat2), function(i) m_fn(x = ml.mat2$ground_truth[i], y = ml.mat2$predicted[i]))
#[1] 2 2 1
:
seq_len