Question

How to deal with missing data in binary classification?

Answer 1

hlo mate ✌️

Here are some common ways of dealing with missing data:

1. Encode NAs as -1 or -9999. ...

2. Casewise deletion of missing data. ...

3. Replace missing values with the mean/median value of the feature in which they occur. ...

4. Label encode NAs as another level of a categorical variable. ...

5. Run predictive models that impute the missing data.