How does Kumo handle missing values in my dataset?

Kumo identifies missing values as entries that are completely left blank, and will not treat columns marked by special strings (e.g., “NaN”, “none”, “N/A”) as missing values. For numeric columns, missing values are commonly filled with invalid number (e.g., -1) to signify their absence. These entries should be cleared out or left blank if you would like them to be considered as missing data.