Y-randomization in KNIME

Previously, I had wrote about how to perform y-randomization in Rapidminer. You can also use those basic concepts to do y-randomization in KNIME. Unlike the previous post where I detailed the steps for an entire y-randomization experiment, in this post, I will show how to perform a single y-randomization on a dataset only. Below is the basic workflow.

“Column Filter” is used to remove all variables except the label. This is then passed to “Shuffle” to randomize the labels. An increasing row id number is then added to this randomized label dataset and the original dataset using “Math Formula”.

“Row ID” is then used to replace the original row ids in both original and randomized label dataset with the newly created row id.

Finally, “Joiner” is used to merge the two datasets together, creating a randomized dataset.