R Programming: Predicting Outliers

0 votes

I'm creating a R program for predicting the outliers in my data set and I'm trying to cut each row containing outliers from my existing data set and putting it in another file.

This is my code:

library(outliers)
for(i in 2:25)
{
  outlier[i]=outlier(Dummy[i], logical=TRUE)
  find_outlier[i]=which(outlier[i]==TRUE,arr.ind=TRUE)
  new_outlier[i]=Dummy[find_outlier[,i]]
}

When I run this code for one variable it works properly. But when I embed this code into a loop it does not work. 

What is the problem here?

Jan 28, 2019 in Data Analytics by Tyrion anex
• 8,380 points
160 views

1 answer to this question.

0 votes

You can remove outliers without a loop, try this:

Student <- c("A", "B", "C", "D", "E")
Test1 <- c(45, 36, 41, 42, 15)
Test2 <- c(47, 42, 38, 34, 44)
Test3 <- c(39, 41, 35, 21, 48)
Test4 <- c(13, 45, 42, 35, 37)
Test5 <- c(36, 38, 42, 14, 47)
Dummy <- data.frame(Student, Test1, Test2, Test3, Test4, Test5)
out <- outlier(Dummy[,2:6], logical=TRUE)
out <- cbind(FALSE, out)
# Actual outlier values
Dummy[which(out[,], TRUE)]
# Row and column numbers of the outliers
which(out[,], TRUE)
answered Jan 28, 2019 by Sophie may
• 9,940 points

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