How to deal with missing continuous data So I have a dataset where I have a continuous variable for only about 10% of the entries. How would you incorporate this in a model. Imputing does not make much sense to me, because there are so few values, however for those entries where I do have it, it is quite an important feature.
Where ever you don't have an entry just make that to a null value or a random unique value. an then create another column, make that column data equal to 1 if data is present 0 otherwise so, the model may learn about that unique imputation and data using another column we are adding.