I am working on the dataset, which has a lot of missing values. I wanted to use from fancyimpute import IterativeImputer to handle the missing values. I am using the imputer as follows,
imputer = IterativeImputer()
imputed_db = imputer.fit_transform(X_missing)
My X_missing has 350 rows and almost 1000 feature columns. As soon as I run my script, my system gets crashes within a minute with a "killed" message. While checking the memory usage, I learned that during the imputation process, my RAM memory usage is high. It would be greatly appreciated if someone can provide me with a workaround for this problem.
Thank you!