我有一些处理这个问题的想法，但我希望guRus可以提供更好的东西。我向Mechanical Turk提交了一堆行输入。我需要一个表中的一行，我有一个字段，我要求他们输入用逗号分隔的行的值。在R中，我已经开始研究这个，现在我正在比较多个Turkers的条目的结果。
一个常见的模式是，一个Turker将错过一个条目，将其余条目抛弃一个。因此，挑战在于知道将缺失值放在何处。假设他们只错过输入一个条目（我有错误检查代码来确认这一点），并且我可能从每个表行获得了最多3个重复（因此可能有1-2个正确的长度，并且1-2太短了。参赛作品的大小差不多，我只有50左右，所以计算效率不是最重要的。假设最长的参赛作品是合适的长度。
以下是一个这样的行的示例（存储为列表，每个元素由不同的Turker复制）：
tt <- list(structure(c(4, 4, 5, 7, 9, 13, 15, 18, 20, 22, 24,
27, 30, 32, 35, 37, 41, 43, 46, 48, 51, 54, 57, 60, 63), .Dim = c(25L,
1L)), structure(c(4, 4, 5, 7, 9, 11, 13, 15, 18, 20, 22, 25,
27, 30, 32, 35, 37, 40, 43, 46, 48, 51, 54, 57, 60, 63), .Dim = c(26L,
1L)), structure(c(4, 4, 5, 7, 9, 11, 13, 15, 19, 20, 22, 25,
27, 30, 32, 35, 37, 42, 43, 46, 48, 51, 54, 57, 61, 63), .Dim = c(26L,
1L)))
lengths <- sapply(tt,length)
longs <- simplify2array(tt[lengths==max(lengths)],FALSE)
shorts <- simplify2array(tt[lengths==max(lengths)-1],FALSE)
我考虑过的算法是：
max(lengths)个排列，并使用一些估计的总偏差将它们同时与1-2个相应长度进行比较。好奇每个人如何实现这一点。我很难避免循环并以优雅的方式编写它。可能像filter这样的东西可能会有所帮助。
有问题的输入和所需输出的示例
有问题的输入（缺少一个值;其他值中没有拼写错误）
> tt1 <- list(c(4, 4, 7, 9, 11), c(4, 4, 5, 7, 9, 11), c(4, 4, 5, 7, 9,
11))
> tt1
[[1]]
[1] 4 4 7 9 11
[[2]]
[1] 4 4 5 7 9 11
[[3]]
[1] 4 4 5 7 9 11
所需的输出
> tt1
[,1] [,2] [,3]
1 4 4 4
2 4 4 4
3 NA 5 5
4 7 7 7
5 9 9 9
6 11 11 11
有问题的输入（缺失值+另一个值中的拼写错误）
> tt2 <- list(c(4, 4, 7, 9, 11), c(4, 3, 5, 7, 9, 11), c(4, 4, 5, 7, 9,
11))
> tt2
[[1]]
[1] 4 4 7 9 11
[[2]]
[1] 4 3 5 7 9 11
[[3]]
[1] 4 4 5 7 9 11
所需的输出
> tt2[[1]][4:6] <- tt2[[1]][3:5]
> tt2[[1]][3] <- NA
> simplify2array(tt2,FALSE)
[,1] [,2] [,3]
[1,] 4 4 4
[2,] 4 3 4
[3,] NA 5 5
[4,] 7 7 7
[5,] 9 9 9
[6,] 11 11 11
应该容忍其他拼写错误的变体。请注意，矢量通常会增加（您可以将它们视为随噪声单调增加）。因此，如果有人错误地认为7为4，那可能是一个错字。还要注意，对于大多数我只做了2次重复，所以没有任何方法可以给予一个非缺失值比任何其他非缺失值更可靠。必须要考虑整个模式，或者至少利用它们普遍增加的事实。
完整数据框
上面的每个tt示例都是下面data.frame中给定脚图像级别的所有TotalTime条目。这是整个数据集。请注意，image组之间的条目总数可能会发生变化。这个值是事先知道的，或者你可以从条目的最大值中得到它。
dat <- structure(list(feet = c(1, 2, 3, 3, 1, 1, 7, 7, 8, 9, 9, 1, 1,
2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6,
6, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 6, 6, 7, 7, 8, 8, 9, 10, 10
), TotalTime = c("4,3,4,6,6,10,12,14,16,18,20,22,25,28,30,32,34,36,41,44,46,49,51,55,58",
"4,4,5,7,9,11,13,15,18,20,22,25,27,30,32,35,37,41,43,46,48,51,54,57,60,63",
"3,4,6,8,11,13,15,17,20,22,25,27,32,34,38,39,41,44,47,49,52,55,58,61,64,67",
"3,4,6,8,11,13,15,17,20,22,25,27,32,34,36,39,41,44,47,49,52,55,58,61,64,67",
"4,3,4,6,8,20,22,24,26,28,30,31,34,36,38,40,42,44,46,48,50,52,54,56,58,60",
"4,3,4,6,8,10,12,14,16,18,20,22,25,28,30,32,34,38,41,44,46,49,51,55,58",
"4,4,4,7,10,15,18,21,24,29,32,35,38,43,47,52,56,60,63,67,72,76,82,84",
"4,4,4,7,10,15,18,21,24,29,32,35,38,43.47,52,56,60,63,67,72,76,82,84",
"4,3,5,8,14,16,20,24,27,31,34,37,42,46,49,55,59,64,68,73,77,83,89,91",
"4,4,6,9,15,18,22,25,28,32,36,40,44,49,53,59,63,68,74,80,85,93,94",
"4,4,6,9,15,18,22,25,28,32,36,40,44,49,53,59,63,68,74,80,85,88,93,94",
"4,3,4,6,8,10,12,14,16,18,20,22,25,28,30,32,34,36,41,44,46,49,51,55,58",
"4,3,4,6,8,10,12,14,16,18,20,22,25,28,30,32,34,36,38,41,44,46,49,51,55,58",
"4,4,5,7,9,11,13,15,18,20,22,25,27,31,32,35,37,41,43,46,48,51,54,57,60,63",
"4,4,5,7,9,11,13,15,18,20,22,25,27,30,32,35,37,41,43,46,48,51,54,57,60,63",
"3,4,6,8,11,13,15,17,20,22,25,27,32,34,38,39,41,44,47,49,52,55,58,61,64,67",
"3,4,6,8,11,13,15,17,20,22,25,27,32,34,36,39,41,44,47,49,52,55,58,61,64,67",
"3,5,7,9,12,14,16,19,22,24,29,31,34,36,38,41,44,47,50,53,58,61,64,67,69,72",
"3,5,7,9,12,14,16,19,22,24,29,31,34,36,38,41,44,47,50,53,58,61,64,67,69,72",
"4,6,8,11,13,15,19,21,25,28,30,33,36,38,41,44,49,52,55,58,61,65,68,71,75,79",
"4,6,8,11,13,15,19,21,25,28,30,33,36,38,41,44,49,52,55,58,61,65,68,71,75,79",
"4,6,9,11,14,17,21,24,27,30,33,35,38,42,45,49,52,55,58,63,67,70,73,78,82,85",
"4,6,9,11,14,17,21,24,27,30,33,35,36,42,45,49,52,55,58,63,67,70,73,78,82,85",
"2,4,6,9,11,13,16,16,20,23,24,26,28,29,31,33,35,37,39,40,42,43,45,47,52",
"2,4,6,9,11,13,16,18,20,21,23,24,26,28,29,31,33,35,37,39,40,42,43,45,47,52",
"2,5,7,11,12,14,17,19,21,22,24,26,28,29,31,35,36,39,41,42,44,46,48,50,52,54",
"2,5,7,11,12,14,17,19,21,22,24,26,28,29,31,35,36,39,41,42,44,46,48,50,52,54",
"4,6,9,11,13,16,18,20,22,24,27,29,31,32,35,37,39,41,43,45,46,49,51,53,55,57",
"4,6,9,11,13,16,18,20,22,24,27,29,31,32,35,37,39,41,43,45,46,49,51,53,55,57",
"6,7,10,13,15,18,20,23,24,28,30,32,34,37,39,41,43,45,47,49,54,57,59,61,63",
"6,7,10,13,15,18,20,23,24,26,28,30,32,34,37,39,41,43,45,47,49,54,57,59,61,63",
"6,8,10,14,16,19,21,23,25,28,30,32,36,39,41,43,45,47,49,52,54,57,59,61,63,65",
"6,8,10,14,16,19,21,23,25,28,30,32,36,39,41,43,45,47,49,52,54,57,59,61,63,65",
"7,9,12,14,18,20,23,24,27,31,33,35,38,40,43,45,47,49,51,55,58,60,62,65,67,69",
"7,9,12,14,18,20,23,24,27,31,33,35,38,40,43,45,47,49,51,55,58,60,62,65,67,69",
"4,3,5,7,10,13,17,20,23,26,29,33,36,40,43,48,51,55,60,64,67,72,75,77",
"4,3,5,7,10,13,17,20,23,26,29,33,36,40,43,48,51,55,60,64,67,72,75,77",
"4,4,4,7,10,15,18,21,24,29,32,35,38,43,47,52,56,60,63,67,72,76,82,84",
"4,4,4,7,10,15,18,21,24,29,32,35,38,43,47,52,56,60,63,67,72,76,82,84",
"4,3,5,8,14,16,20,24,27,31,34,37,42,46,49,55,59,64,68,73,77,83,89,91",
"4,3,5,8,14,16,20,24,27,31,34,37,42,46,49,55,59,64,68,73,77,83,89,91",
"4,4,6,9,15,18,22,25,28,32,36,40,44,49,53,59,63,68,74,80,85,88,93,94",
"4,4,6,9,15,18,22,25,28,32,36,40,44,49,53,59,63,68,74,80,85,88,93,94",
"0,0,0,1,1,1,3,3,3,5,5,5,6,6,7,7,8,8,9,10,11,10,11,11", "0,0,0,1,1,1,3,3,3,5,5,6,6,7,7,8,8,9,10,11,10,11,11",
"6,4,7,10,13,16,20,22,25,27,30,32,35,38,43,45,48,52,54,57,60,62,64,67",
"6,4,7,10,13,16,20,22,25,27,30,32,35,38,43,45,48,52,54,57,60,62,64,67",
"6,4,7,10,14,19,21,23,26,28,33,36,39,42,45,47,50,53,56,60,62,65,69,70",
"6,4,7,10,14,19,21,23,26,28,33,36,39,42,45,47,50,53,56,60,62,65,69,70",
"2,5,9,12,14,20,21,24,29,32,34,37,41,44,46,50,53,59,62,65,68,72,75,76",
"2,5,9,12,14,20,21,24,29,32,34,37,41,44,46,50,53,59,62,65,68,72,75,76",
"2,5,9,13,17,20,24,27,30,33,37,42,45,48,52,55,58,62,65,67,72,75,78,80",
"3,6,10,15,18,23,25,26,28,32,36,40,43,47,50,53,58,61,65,67,70,75,78,83,86",
"3,6,10,15,18,23,25,28,32,36,40,43,47,50,53,58,61,65,67,70,75,78,83,86"
), image = c(1, 1, 1, 1, 3, 3, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4)), .Names = c("feet",
"TotalTime", "image"), row.names = c(1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 14L, 15L, 16L, 17L, 19L, 20L, 22L, 23L,
24L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L,
38L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 49L, 50L, 51L, 53L,
54L, 55L, 56L, 57L, 58L, 59L, 61L, 62L, 63L), class = "data.frame")
答案 0 :(得分：1)
我希望这会有所帮助：
f <- function(tt) {
len <- (sapply(tt, length))
tar <- rowMeans(do.call("cbind", tt[len == max(len)]))
tt[len < max(len)] <-
lapply(tt[len < max(len)],
function(x) {
r <- lapply(combn(max(len), max(len)-length(x)),
function(i) {z <- numeric(max(len)); z[i] <- NA; z[!is.na(z)] <- x; z})
r[[which.min(sapply(r, function(x) sum((x - tar)^2, na.rm = T)))]]
})
simplify2array(tt,FALSE)
}
然后，
> f(tt)
[,1] [,2] [,3]
[1,] 4 4 4
[2,] 3 4 4
[3,] 4 5 5
... snip ...
[24,] 55 57 57
[25,] 58 60 61
[26,] NA 63 63
> f(tt1)
[,1] [,2] [,3]
[1,] 4 4 4
[2,] 4 4 4
[3,] NA 5 5
[4,] 7 7 7
[5,] 9 9 9
[6,] 11 11 11
> f(tt2)
[,1] [,2] [,3]
[1,] 4 4 4
[2,] 4 3 4
[3,] NA 5 5
[4,] 7 7 7
[5,] 9 9 9
[6,] 11 11 11
以下是您的完整数据的示例：
dlply(dat, .(feet, image), function(x) f(lapply(strsplit(x$TotalTime, ","), as.numeric)))
看起来运作良好。
答案 1 :(得分：1)
这是一个旨在可读的解决方案。毫无疑问，它可以折叠成少量的代码行：
desiredLength <- function(x){
len <- sapply(x, length)
max(len)
}
insertNA <- function(x, position=1){
c(x[seq_along(x) < position], NA, x[seq_along(x) >= position])
}
fixLength <- function(x, position=1){
dlen <- desiredLength(x)
sapply(x, function(zz) if(length(zz) < dlen) insertNA(zz, position) else zz)
}
objectiveFunction <- function(x){
sum(apply(x, 1, function(z)length(unique(z))))
}
findMinObjective <- function(x){
pos <- NA
obj <- Inf
for(i in 1:desiredLength(x)){
z <- objectiveFunction(fixLength(x, position=i))
if(z < obj){
obj <- z
pos <- i
}
}
fixLength(x, pos)
}
结果：
> findMinObjective(tt1)
[,1] [,2] [,3]
[1,] 4 4 4
[2,] 4 4 4
[3,] NA 5 5
[4,] 7 7 7
[5,] 9 9 9
[6,] 11 11 11
> findMinObjective(tt2)
[,1] [,2] [,3]
[1,] 4 4 4
[2,] 4 3 4
[3,] NA 5 5
[4,] 7 7 7
[5,] 9 9 9
[6,] 11 11 11