Hi,
I am sorry, could you tell me exactly how. I understand I am troubling you but 
im trying to learn R since the last two weeks and haven’t been able to come 
to terms with the suble nuances.

Thanks again,
doy

From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
Behalf Of Jessica Streicher
Sent: Thursday, April 26, 2012 5:07 PM
To: r-help@r-project.org
Subject: Re: [R] Splitting data into test and train (80:20) kepping attributes 
similar

Be reminded that s1 and s2 are only the indexes on AD_0 and AD_1 of the data 
which you want to keep.

therefore

traindata <- rbind(s1,s2)

will not work.

you need to take data from AD_0 and AD_0 for that, similarly with what you did 
with s3 and s4.


Am 26.04.2012 um 12:56 schrieb Dwaipayan Dasgupta:

> Hi ,
> Thanks again for helping me out.
> Here is the code I am using
> Ad_1 <- subset(Attrition_data_1,Attrition_ind=="1")
> Ad_0 <- subset(Attrition_data_1,Attrition_ind=="0")
>
> s1<-sample(1:dim(Ad_0)[1],0.8*dim(Ad_0)[1])# 80% of the non-attrites
> s2<-sample(1:dim(Ad_1)[1],0.8*dim(Ad_1)[1])# 80% of attritees
>
> s3<- Ad_0 [-s1,]
> summary(s3)
>
> s4<- Ad_1 [-s2,]
> summary(s4)
>
> traindata <- rbind(s1,s2)
> testdata <- rbind(s3,s4)
>
> this works for the test dataset but throws up an error of
> Warning message:
> In rbind(s1, s2) :
>   number of columns of result is not a multiple of vector length (arg 2)
>
> I understand that I am trying to append vectors of unequal vector lengths but 
> don�t know how to work around this process.
> Would you help please
>
> Thanks,
> Dwaipayan
>
> From: Jessica Streicher [mailto:j.streic...@micromata.de]
> Sent: Wednesday, April 25, 2012 9:25 PM
> To: Dwaipayan Dasgupta
> Cc: r-help@r-project.org
> Subject: Re: [R] Splitting data into test and train (80:20) kepping 
> attributes similar
>
> Don't know whats wrong there (except if you're using the eclipse R plugin on 
> a mac like me and the window for choosing the download site doesn't pop up..  
> did it?^^)
>
> Anyway, you could just split all of your data into 2 datasets, one that has 
> all the data labeled 0, the other for all labeled 1, then take a random 80% 
> of both, put them back together into the 80% data, and put the rest back 
> together to form the 20%.
>
> Since i don't know your data, heres an example:
> M<-cbind(c(rep(0,10),rep(1,10)),1:20)
> > M
>       [,1] [,2]
>  [1,]    0    1
>  [2,]    0    2
>  [3,]    0    3
>  [4,]    0    4
>  [5,]    0    5
>  [6,]    0    6
>  [7,]    0    7
>  [8,]    0    8
>  [9,]    0    9
> [10,]    0   10
> [11,]    1   11
> [12,]    1   12
> [13,]    1   13
> [14,]    1   14
> [15,]    1   15
> [16,]    1   16
> [17,]    1   17
> [18,]    1   18
> [19,]    1   19
> [20,]    1   20
>
> index1<-which(M[,1]==1)
> > index1
>  [1] 11 12 13 14 15 16 17 18 19 20
>
> > M1<-M[index1,]
> > M1
>       [,1] [,2]
>  [1,]    1   11
>  [2,]    1   12
>  [3,]    1   13
>  [4,]    1   14
>  [5,]    1   15
>  [6,]    1   16
>  [7,]    1   17
>  [8,]    1   18
>  [9,]    1   19
> [10,]    1   20
>
> > M0<-M[-index1,]
> > M0
>       [,1] [,2]
>  [1,]    0    1
>  [2,]    0    2
>  [3,]    0    3
>  [4,]    0    4
>  [5,]    0    5
>  [6,]    0    6
>  [7,]    0    7
>  [8,]    0    8
>  [9,]    0    9
> [10,]    0   10
>
> > s1<-sample(1:dim(M1)[1],0.8*dim(M1)[1])
> > s1
> [1] 10  3  5  9  2  6  8  7
>
> > s0<-sample(1:dim(M0)[1],0.8*dim(M0)[1])
> > s0
> [1]  8 10  9  3  7  4  2  1
>
> > data80<-rbind(M1[s1,],M0[s0,])
> > data80
>       [,1] [,2]
>  [1,]    1   20
>  [2,]    1   13
>  [3,]    1   15
>  [4,]    1   19
>  [5,]    1   12
>  [6,]    1   16
>  [7,]    1   18
>  [8,]    1   17
>  [9,]    0    8
> [10,]    0   10
> [11,]    0    9
> [12,]    0    3
> [13,]    0    7
> [14,]    0    4
> [15,]    0    2
> [16,]    0    1
>
> > data20<-rbind(M1[-s1,],M0[-s0,])
> > data20
>      [,1] [,2]
> [1,]    1   11
> [2,]    1   14
> [3,]    0    5
> [4,]    0    6
>
>
> which is probably not how you really do things efficiently, but it should 
> work.
>
> greetings
> Jessi
>
>
> Am 25.04.2012 um 17:18 schrieb Dwaipayan Dasgupta:
>
>
> Thank you so much for replying. I tried what you said but it still throws the 
> same error i.e could not find function "sample.split"
> Might be because of the version of R I am running (R version 2.12.2).i do not 
> have admin rights to upgrade to the newest version.
> Is there anything else I can try? Im trying to split my data into 80:20 
> keeping the ratio of 0,1 in the Y variable(binary) constant.
>
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
> Behalf Of Jessica Streicher
> Sent: Wednesday, April 25, 2012 7:17 PM
> To: r-help@r-project.org
> Subject: Re: [R] Splitting data into test and train (80:20) kepping 
> attributes similar
>
> Well, it throws an error, because there is no such function in default R. A 
> bit of googling showed it might be the one in the caTools package.
>
> execute this:
> install.packages("caTools")
> library(caTools)
>
> before executing your code
>
>
> Am 25.04.2012 um 12:39 schrieb Dwaipayan Dasgupta:
>
>
> Hi,
> Could someone help me with this please , im trying to use
> Y = Attrition_data[,1] # extract labels from the data
> msk = sample.split (Y, SplitRatio=3/4)
> table(Y,msk)
> to do the splitting but it keeps throwing up and error
> Error: could not find function "sample.split"
> Could you please help
>
> Thanks in advance
> doy
>
>
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
> Behalf Of Dwaipayan Dasgupta
> Sent: Tuesday, April 24, 2012 9:08 PM
> To: r-help@r-project.org
> Subject: [R] Splitting data into test and train (80:20) kepping attributes 
> similar
>
> Hi,
> I am trying to do some predictive modeling around attrition and want to split 
> the dataset into test and train (80:20) and keep the ratio of attritees:non 
> attrites same.
> In my dataset the attrition indicator is coded as 0(for non-attritees) and 1 
> (for attritees) and I want to keep the ratio of 0's to 1 similar.
> I apologize for this trivial question but this is my second week with R.
>
> Thanks,
> Doy
>
>
>
>
>
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