[R] Saving misclassified records into dataframe within a loop
David Winsemius
dwinsemius at comcast.net
Fri May 13 00:37:59 CEST 2011
On May 12, 2011, at 6:26 PM, John Dennison wrote:
> My apologies. I have transgressed the first law of posting, test
> your code. here is an updated set this should run:
>
> library(rpart)
>
> # grow tree
> fit <- rpart(Kyphosis ~ Age + Number + Start,
> method="class", data=kyphosis)
> #predict
> prediction<-predict(fit, kyphosis)
>
> #create output data.frame
> results<-as.data.frame(1)
>
>
> #misclassification index function
>
> predict.function <- function(x){
> j<-0
>
> for (i in 1:length(kyphosis$Kyphosis)) {
> if (((kyphosis$Kyphosis[i]=="absent")==(prediction[i,1]==1)) == 0 ){
I think your next task is figuring out if this expression ,,,, which
you have not explained at all ... is really doing what you intend:
(kyphosis$Kyphosis[i]=="absent")==(prediction[i,1]==1)) == 0
I would have guessed that you might be intending:
kyphosis$Kyphosis[i]=="absent" & prediction[i,1]==1
Since it will hold about half the time:
> sum(kyphosis$Kyphosis[1:81]=="absent" & prediction[1:81,1]==1)
[1] 41
>
> j<-j+1
> results[j,]<-row.names(kyphosis[c(i),])
>
> print( row.names(kyphosis[c(i),]))
> } }
> {
> print(results)
> save(results, file="results") } }
>
>
> predict.function(x)
>
>
> results
>
> output: results
> 1
> 1 1
>
>
> load("results")
>
> results
> > results
> 1
> 1 1
> 2 2
> 3 4
> 4 13
> 5 18
> 6 24
> 7 27
> 8 28
> 9 32
> 10 33
> 11 35
> 12 43
> 13 44
> 14 48
> 15 50
> 16 51
> 17 60
> 18 63
> 19 68
> 20 71
> 21 72
> 22 74
> 23 79
>
> why the two different 'results'??
>
> Thanks
>
> John Dennison
>
> On Thu, May 12, 2011 at 6:06 PM, David Winsemius <dwinsemius at comcast.net
> > wrote:
>
> On May 12, 2011, at 5:41 PM, John Dennison wrote:
>
> Having poked the problem a couple more times it appears my issue is
> that the
> object i save within the loop is not available after the function
> ends. I
> have no idea why it is acting in this manner.
>
>
> library(rpart)
>
> # grow tree
> fit <- rpart(Kyphosis ~ Age + Number + Start,
> method="class", data=kyphosis)
> #predict
> prediction<-predict(fit, kyphosis)
>
> #misclassification index function
>
> results<-as.data.frame(1)
>
> predict.function <- function(x){
> j<-0
> for (i in 1:length(kyphosis$Kyphosis)) {
> if (((kyphosis$Kyphosis[i]=="absent")==(prediction[i,1]==1)) == 0 ){
>
> j<-j+1
> results[j,]<-row.names(testing[c(i),])
>
> Are we supposed to know where to find 'testing" (and if we cannot
> find it, how is the R interpreter going to find it)?
>
>
>
> print( row.names(kyphosis[c(i),]))
> } }
> {
> print(results)
> save(results, file="results") } }
>
>
> i can load results from file and my out put is there. how ever if i
> just
> type results i get the original 1. what is in the lords name is
> occurring.
>
> Thanks
>
> John
>
>
>
> On Thu, May 12, 2011 at 1:50 PM, Phil Spector <spector at stat.berkeley.edu
> >wrote:
>
> John -
> In your example, the misclassified observations (as defined by
> your predict.function) will be
>
> kyphosis[kyphosis$Kyphosis == 'absent' & prediction[,1] != 1,]
>
> so you could start from there.
> - Phil Spector
> Statistical Computing Facility
> Department of Statistics
> UC Berkeley
> spector at stat.berkeley.edu
>
>
>
> On Thu, 12 May 2011, John Dennison wrote:
>
> Greetings R world,
>
> I know some version of the this question has been asked before, but
> i need
> to save the output of a loop into a data frame to eventually be
> written to
> a
> postgres data base with dbWriteTable. Some background. I have
> developed
> classifications models to help identify problem accounts. The logic is
> this,
> if the model classifies the record as including variable X and it
> turns
> out
> that record does not have X then it should be reviewed(ie i need the
> row
> number/ID saved to a database). Generally i want to look at the
> misclassified records. This is a little hack i know, anyone got a
> better
> idea please let me know. Here is an example
>
> library(rpart)
>
> # grow tree
> fit <- rpart(Kyphosis ~ Age + Number + Start,
> method="class", data=kyphosis)
> #predict
> prediction<-predict(fit, kyphosis)
>
> #misclassification index function
>
> predict.function <- function(x){
> for (i in 1:length(kyphosis$Kyphosis)) {
> #the idea is that if the record is "absent" but the prediction is
> otherwise
> then show me that record
> if (((kyphosis$Kyphosis[i]=="absent")==(prediction[i,1]==1)) == 0 ){
> #THIS WORKS
> print( row.names(kyphosis[c(i),]))
> }
> } }
>
> predict.function(x)
>
> Now my issue is that i want to save these id to a data.frame so i can
> later
> save them to a database. This this an incorrect approach. Can I save
> each
> id
> to the postgres instance as it is found. i have a ignorant fear of
> lapply,
> but it seems it may hold the key.
>
>
> Ive tried
>
> predict.function <- function(x){
> results<-as.data.frame(1)
> for (i in 1:length(kyphosis$Kyphosis)) {
> #the idea is that if the record is "absent" but the prediction is
> otherwise
> then show me that record
> if (((kyphosis$Kyphosis[i]=="absent")==(prediction[i,1]==1)) == 0 ){
> #THIS WORKS
> results[i,]<- as.data.frame(row.names(kyphosis[c(i),]))
> }
> } }
>
> this does not work. results object does not get saved. Any Help
> would be
> greatly appreciated.
>
>
> Thanks
>
> John Dennison
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
> David Winsemius, MD
> West Hartford, CT
>
>
David Winsemius, MD
West Hartford, CT
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