#38 Machine Learning & Data Science Challenge 38

#38 Machine Learning & Data Science Challenge 38

What do you do if there are outliers?

The following are the approaches to handling the outliers:

  1. Drop the outlier records.

  2. Assign a new value: If an outlier seems to be due to a mistake in your data, you try imputing a value.

  3. If percentage-wise the number of outliers is less, but when we see numbers, there are several, then, in that case, dropping them might cause a loss in insight. We should group them in that case and run our analysis separately on them.