AV Practice Problem Loan Prediction



I am trying this practice problem. Someone suggested me to use ensemble techniques. How do I use ensemble techniques on a categorical variable? Loan_Status is a categorical variable with only two outcomes ‘Y’ and ‘N’.
Is it possible by giving hypothetical number to ‘Y’ and ‘N’?


@gau2112 - You can make different models like a random forest, boosting and decision tree and create a data frame of each model and use mode function to select a maximum occurring value for each observation from a different model.

For example
    # adding output of different model to make a single data frame  name as submit_match3
    submit_match3$cuisine2 <- submit_match2$cuisine 
    submit_match3$cuisine1 <- submit_match1$cuisine

     MODE function to extract the predicted value with the highest frequency per id.

    #function to find the maximum value row wise
    Mode <- function(x) {
    u <- unique(x)
    u[which.max(tabulate(match(x, u)))]
    x <- Mode(submit_match3[,c("cuisine","cuisine2","cuisine1")])
    y <- apply(submit_match3,1,Mode)

Hope this helps!



Thanks a lot.


For Python, use following EnsembleClassifier that combines different models.
Check below URL who developed this module and also explained with examples.


hey.can someone please share the solution in R. If possible please mail.It will be really helpful. TIA!