R help - Nov 2011 - Subsampling-oversampling from a data frame

If no one has a better solution, split it, take a sample of size X from both
and put it back together.


hgwelec wrote:
> 
> Dear members,
> 
> Consider the following data frame (first 4 rows shown)
> 
> 
>   age sex class
>   15   m   low
>   20   f  high
>   15   f   low
>   10   m   low
> 
> in my original data set i have 1200 rows and a class distribution of
> low=0.3 and high=0.7
> 
> 
> My question : how can i create a new data frame as the one shown above but
> with the 'high' class subsampled so that in the new data frame the
class
> distribution is low=0.5 and high=0.5?
> 
> I tried looking at the sample function and prob option but all examples i
> seen do not use an imbalanced class problem as the one shown above
> 
> 
> Thank you in advance
> 
> 
> Thank you in advance
> 

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# Perhaps I misunderstand your original need, but....


## I added a few lines to your data and used dput() to get the below data (I
named "df")

df<- structure(list(age = c(15L, 20L, 15L, 10L, 10L, 12L, 17L, 17L, 
11L, 12L, 16L, 20L, 23L, 14L, 22L, 16L, 10L, 11L, 21L, 10L, 13L, 
17L), sex = structure(c(2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 
2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L), .Label = c("f", 
"m"), class = "factor"), class = structure(c(2L, 1L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 
2L, 1L), .Label = c("high", "low"), class =
"factor")), .Names = c("age",
"sex", "class"), class = "data.frame", row.names =
c(NA, -22L
))

## the following line uses which(), sample(), and rbind(), along with some
indexing to get a new dataframe; see ?which, ?sample, and ?rbind for more
info
# For the "indexing", play with it, ... type in df[1:3,1:2] as an
example

new_df <- rbind(df[sample(which(df$class=="low"), 4),],
df[sample(which(df$class=="high"), 4),])

Now replace 4 with the the size of each you want.




hgwelec wrote:
> 
> Thank you for your answer.
> 
> The problem is that i am learning R now, so i do not know how i could do
> this.
> 
> 
> I have found the following code but it does not work unfortunately
> (=create distribution 0.1 "low" class - 0.9 high) :
> 
> 
> 
> data[c(rownames(data.df[data.df$class=="high",]),
> sample(rownames(data[data.df$class=="low"]), 0.1)) , ]
> 




2 posts
This post has NOT been accepted by the mailing list yet.
Dear members, 

Consider the following data frame (first 4 rows shown) 


  age sex class 
  15   m   low 
  20   f  high 
  15   f   low 
  10   m   low 

in my original data set i have 1200 rows and a class distribution of low=0.3
and high=0.7 


My question : how can i create a new data frame as the one shown above but
with the 'high' class subsampled so that in the new data frame the class
distribution is low=0.5 and high=0.5? 

I tried looking at the sample function and prob option but all examples i
seen do not use an imbalanced class problem as the one shown above 


Thank you in advance 


Thank you in advance   



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