R help - May 2009 - Using sample to create Training and Test sets

Forgive the newbie question, I want to select random rows from my 
data.frame to create a test set (which I can do) but then I want to 
create a training set using whats left over.

Example code:
acc <- read.table("accOUT.txt", header=T, sep = ",",
row.names=1)
#select 400 random rows in data
training <- acc[sample(1:nrow(acc), 400, replace=TRUE),]

#try to get whats left of acc not in training
testset <- acc[-training, ]
Fails with the following error....
Error: invalid subscript type
In addition: Warning message:
- not meaningful for factors in: Ops.factor(left)

I then try.
testset <- acc[!training, ]
Which gives me the warning message
! not meaningful for factors in: Ops.factor(left)
And if i look at testset It is 400 rows of NA's ... which clearly isn't 
right.

Can anyone tell me what I'm doing wrong.

Thanks in advance

Chris

Note that the single split sample technique is not competitive with 
other approaches unless the sample size exceeds around 20,000.

Frank


Chris Arthur wrote:
> Forgive the newbie question, I want to select random rows from my 
> data.frame to create a test set (which I can do) but then I want to 
> create a training set using whats left over.
> 
> Example code:
> acc <- read.table("accOUT.txt", header=T, sep = ",",
row.names=1)
> #select 400 random rows in data
> training <- acc[sample(1:nrow(acc), 400, replace=TRUE),]
> 
> #try to get whats left of acc not in training
> testset <- acc[-training, ]
> Fails with the following error....
> Error: invalid subscript type
> In addition: Warning message:
> - not meaningful for factors in: Ops.factor(left)
> 
> I then try.
> testset <- acc[!training, ]
> Which gives me the warning message
> ! not meaningful for factors in: Ops.factor(left)
> And if i look at testset It is 400 rows of NA's ... which clearly
isn't
> right.
> 
> Can anyone tell me what I'm doing wrong.
> 
> Thanks in advance
> 
> Chris
> 
-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

Here's one possibility:

idx <- sample(nrow(acc))
training <- acc[idx[1:400], ]
testset <- acc[-idx[1:400], ]

Andy

From: Chris Arthur
> 
> Forgive the newbie question, I want to select random rows from my 
> data.frame to create a test set (which I can do) but then I want to 
> create a training set using whats left over.
> 
> Example code:
> acc <- read.table("accOUT.txt", header=T, sep = ",",
row.names=1)
> #select 400 random rows in data
> training <- acc[sample(1:nrow(acc), 400, replace=TRUE),]
> 
> #try to get whats left of acc not in training
> testset <- acc[-training, ]
> Fails with the following error....
> Error: invalid subscript type
> In addition: Warning message:
> - not meaningful for factors in: Ops.factor(left)
> 
> I then try.
> testset <- acc[!training, ]
> Which gives me the warning message
> ! not meaningful for factors in: Ops.factor(left)
> And if i look at testset It is 400 rows of NA's ... which 
> clearly isn't 
> right.
> 
> Can anyone tell me what I'm doing wrong.
> 
> Thanks in advance
> 
> Chris
> 
> ______________________________________________
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>> Forgive the newbie question, I want to select random rows from my
>> data.frame to create a test set (which I can do) but then I want to
>> create a training set using whats left over.
>>
The caret package has a function, createDataPartition, that does the
split taking into account the distribution of the outcome. This might
be good in classification cases where one or more classes have low
percentages in the data set.

There is more detail in the pdf:

 http://cran.r-project.org/web/packages/caret/vignettes/caretMisc.pdf

and examples in this pdf

  http://cran.r-project.org/web/packages/caret/vignettes/caretTrain.pdf

Max