How to map predicted values to unique id in dataset? - r

Question

I have written this R code to reproduce. Here, I have a created a unique column "ID", and I am not sure how to add the predicted column back to test dataset mapping to their respective IDs. Please guide me on the right way to do this.
#Code
library(C50)
data(churn)
data=rbind(churnTest,churnTrain)
data$ID<-seq.int(nrow(data)) #adding unique id column
rm(churnTrain)
rm(churnTest)
set.seed(1223)
ind <- sample(2,nrow(data),replace = TRUE, prob = c(0.7,0.3))
train <- data[ind==1,1:21]
test <- data[ind==2, 1:21]
xtrain <- train[,-20]
ytrain <- train$churn
xtest <- test[,-20]
ytest<- test$churn
x <- cbind(xtrain,ytrain)
## C50 Model
c50Model <- C5.0(churn ~
state +
account_length +
area_code +
international_plan +
voice_mail_plan +
number_vmail_messages +
total_day_minutes +
total_day_calls +
total_day_charge +
total_eve_minutes +
total_eve_calls +
total_eve_charge +
total_night_minutes +
total_night_calls +
total_night_charge +
total_intl_minutes +
total_intl_calls +
total_intl_charge +
number_customer_service_calls,data=train, trials=10)
# Evaluate Model
c50Result <- predict(c50Model, xtest)
table(c50Result, ytest)
#adding prediction to test data
testnew = cbind(xtest,c50Result)
#OR predict directly
xtest$churn = predict(c50Model, xtest)

Answer 1

I’d use match(dataID, predictedID) to match ID columns in data sets.
In reply to your comment:
If you want to add predicted values to the original dataframe, both ways of merging data and prediction are correct and produce identical result. The only thing is, I would use
xtest$churn_hut <- predict(c50Model, xtest)
instead of
xtest$churn <- predict(c50Model, xtest)
because here you are replacing original churn ( as in data$churn) with whatever the model predicted, so you can’t compare the two.