8.10 Missing Values

The topic of missing values is a significant topic and is covered elsewhere. For purposes of demonstration missing values are removed from our dataset by imputing (i.e., making up) values for any missing value using randomForest::na.roughfix().

ds[vars] <- na.roughfix(ds[vars])


Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0