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),])
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 <spec...@stat.berkeley.edu>wrote:
> John -
> In your example, the misclassified observations (as defined by
> your predict.function) will be
>
> kyphosis[kyphosis$Kyphosis == 'absent' & prediction[,1] != 1,]
>
> so you could start from there.
> - Phil Spector
> Statistical Computing Facility
> Department of Statistics
> UC Berkeley
> spec...@stat.berkeley.edu
>
>
>
> On Thu, 12 May 2011, John Dennison wrote:
>
> Greetings R world,
>>
>> I know some version of the this question has been asked before, but i need
>> to save the output of a loop into a data frame to eventually be written to
>> a
>> postgres data base with dbWriteTable. Some background. I have developed
>> classifications models to help identify problem accounts. The logic is
>> this,
>> if the model classifies the record as including variable X and it turns
>> out
>> that record does not have X then it should be reviewed(ie i need the row
>> number/ID saved to a database). Generally i want to look at the
>> misclassified records. This is a little hack i know, anyone got a better
>> idea please let me know. Here is an example
>>
>> library(rpart)
>>
>> # grow tree
>> fit <- rpart(Kyphosis ~ Age + Number + Start,
>> method="class", data=kyphosis)
>> #predict
>> prediction<-predict(fit, kyphosis)
>>
>> #misclassification index function
>>
>> predict.function <- function(x){
>> for (i in 1:length(kyphosis$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@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.
>>
>>
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