Sunny - Definitely a great topic that I will expand on later. One thing I like to do is bin continuous variables using something like tree based methods and weights of evidence. You can maintain a separate bin for missing. Binning also helps with extreme values in the tails. I also like using tree based methods that allow the missing values to float or use surrogate rules. One approach you can do with a good SAS compute cluster that is threaded is to use the feature (input) as a predictor and use some of the other features to predict the missing values. All of these are super easy to do in Enterprise Miner with just a simple process flow diagram (what many now call an ML pipeline). Super easy. Outliers is a big topic. Anyway thank for reading my blog.