Missing value Imputation in R



I’m working on the classification problem having close to 6L observations and 60 variables. Variables also having missing values, I have removed the variables with a large number of missing values and trying to impute the missing values for rest of the variables.

I’ve tried the MICE and missForest package from R but it’s taking more time to compute the missing values. How to proceed with missing values imputation, any other approach or algorithm? Do I have to use parallel computation?


Hi @akamboj,

Based on the type of variables that you are working with, there can be different missing value imputation techniques. You can follow the below-given article which explains various techniques to impute missing values present in the dataset:

You can also refer this article to learn about various packages available in R for imputing missing values:


Hi @akamboj,

Try Predictive Mean matching technique…