How to make randomly sampled training sets of proportionately equal sizes?
I want to make a series of randomly sampled training sets that are exactly 75% the size of the full data set. The code below is an example of what I want to achieve except I always want 75 samples of 1, and 25 samples of 2; this code only gives me samples which are close to those sizes but not exact.
column <- c(rep("A", 40), rep("B", 60))
data <- as.data.frame(column)
index <- sample(2,100, replace=TRUE, prob=c(0.75,0.25))
I want to be able to achieve this kind of partitioning without the use of additional packages and just with the base R if possible. Packages don't seem to work for me the vast majority of the time, which is why I have found it difficult to find a solution already.
r
asked Nov 12 '18 at 18:09
Ryan Tandy
103
add a comment |
I want to make a series of randomly sampled training sets that are exactly 75% the size of the full data set. The code below is an example of what I want to achieve except I always want 75 samples of 1, and 25 samples of 2; this code only gives me samples which are close to those sizes but not exact.
column <- c(rep("A", 40), rep("B", 60))
data <- as.data.frame(column)
index <- sample(2,100, replace=TRUE, prob=c(0.75,0.25))
I want to be able to achieve this kind of partitioning without the use of additional packages and just with the base R if possible. Packages don't seem to work for me the vast majority of the time, which is why I have found it difficult to find a solution already.
r
asked Nov 12 '18 at 18:09
Ryan Tandy
103
add a comment |
I want to make a series of randomly sampled training sets that are exactly 75% the size of the full data set. The code below is an example of what I want to achieve except I always want 75 samples of 1, and 25 samples of 2; this code only gives me samples which are close to those sizes but not exact.
column <- c(rep("A", 40), rep("B", 60))
data <- as.data.frame(column)
index <- sample(2,100, replace=TRUE, prob=c(0.75,0.25))
I want to be able to achieve this kind of partitioning without the use of additional packages and just with the base R if possible. Packages don't seem to work for me the vast majority of the time, which is why I have found it difficult to find a solution already.
r
asked Nov 12 '18 at 18:09
Ryan Tandy
103
I want to make a series of randomly sampled training sets that are exactly 75% the size of the full data set. The code below is an example of what I want to achieve except I always want 75 samples of 1, and 25 samples of 2; this code only gives me samples which are close to those sizes but not exact.
column <- c(rep("A", 40), rep("B", 60))
data <- as.data.frame(column)
index <- sample(2,100, replace=TRUE, prob=c(0.75,0.25))
I want to be able to achieve this kind of partitioning without the use of additional packages and just with the base R if possible. Packages don't seem to work for me the vast majority of the time, which is why I have found it difficult to find a solution already.
r
r
asked Nov 12 '18 at 18:09
Ryan Tandy
103
asked Nov 12 '18 at 18:09
Ryan Tandy
103
asked Nov 12 '18 at 18:09
Ryan Tandy
103
asked Nov 12 '18 at 18:09
Ryan Tandy
103
asked Nov 12 '18 at 18:09
Ryan Tandy
103
103
add a comment |
add a comment |
1 Answer
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That's how sample is intended to work. You may instead consider two steps:
idxTrain <- sample(100, 75)
head(idxTrain)
# [1] 54 70 3 42 72 67
length(idxTrain)
# [1] 75
idxTest <- setdiff(1:100, idxTrain)
head(idxTest)
# [1] 5 7 13 14 19 24
length(idxTest)
# [1] 25
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
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active
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That's how sample is intended to work. You may instead consider two steps:
idxTrain <- sample(100, 75)
head(idxTrain)
# [1] 54 70 3 42 72 67
length(idxTrain)
# [1] 75
idxTest <- setdiff(1:100, idxTrain)
head(idxTest)
# [1] 5 7 13 14 19 24
length(idxTest)
# [1] 25
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
add a comment |
That's how sample is intended to work. You may instead consider two steps:
idxTrain <- sample(100, 75)
head(idxTrain)
# [1] 54 70 3 42 72 67
length(idxTrain)
# [1] 75
idxTest <- setdiff(1:100, idxTrain)
head(idxTest)
# [1] 5 7 13 14 19 24
length(idxTest)
# [1] 25
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
add a comment |
That's how sample is intended to work. You may instead consider two steps:
idxTrain <- sample(100, 75)
head(idxTrain)
# [1] 54 70 3 42 72 67
length(idxTrain)
# [1] 75
idxTest <- setdiff(1:100, idxTrain)
head(idxTest)
# [1] 5 7 13 14 19 24
length(idxTest)
# [1] 25
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
That's how sample is intended to work. You may instead consider two steps:
idxTrain <- sample(100, 75)
head(idxTrain)
# [1] 54 70 3 42 72 67
length(idxTrain)
# [1] 75
idxTest <- setdiff(1:100, idxTrain)
head(idxTest)
# [1] 5 7 13 14 19 24
length(idxTest)
# [1] 25
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
answered Nov 12 '18 at 18:16
Julius Vainora
32.4k75979
32.4k75979
add a comment |
add a comment |
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