How does Kumo handle missing values in my dataset?

Column encoders determine how Kumo Engine handles missing values. Numerical encoders support mean imputation, zero imputation, or a separate missing-value representation. Other encoders support different strategies.

Set defaults by semantic type with plan.column_processing.na_strategy, or configure individual columns through encoder_overrides. See Missing Values for supported values and precedence.

Convert placeholders such as -1 or "N/A" to nulls when they represent missing data. Check the source reader’s parsing rules; a sentinel value is not necessarily read as null.