[R] Saving misclassified records into dataframe within a loop

[Phil Spector]

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]]
>
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