I train a decision tree and find out which of my rows have been correctly classified and which wrongly. Sometime everything is “right”, sometime some rows is “right” and some are “wrong” and sometime everything is “wrong” if I train on some extremely small set (e.g. with 3 rows, just to test technical functionality of the flow). Some of the rows are also labeled “train”, as I do not classify my training data (using a Partitioning node before the training and testing). I then parse this column “correctness” to the Color Manager node.
Long story short (TL;DR): I have a String column “correctness” with varying entries for different datasets.
Every time the Color Manager gets different values for “correctness” I need to open it and press “OK”. This is fine on my personal machine, but once I upload the flow to my KNIME Server, this does not work anymore - the flow “does not fully execute”.
Question: How can predefine for the Color Manager what values it should expect and which colors the respective value/rows should have if a particular value is encountered in the “correctness” column?