Handling missing data

Most machine learning algorithms cannot work with missing data. Missing values must be removed, replaced, or inferred.

Use the Handle Missing Data activity and select an option to replace missing data, remove the entire row containing missing data, or impute values using interpolation methods.

If data quantity is abundant, remove entire rows that contain missing values. If data quantity is limited, impute the missing values by replacing them with mean/mode/constant, or by using the offered interpolation methods.