Hi Everyone 
Iām a bit late, but here is my solution to challenge 9:
I have taken the simple approach of using the -Decision Tree Learner- and -Decision Tree Predictor- nodes and treating the challenge as a classification problem.
I have used the -Decision Tree to Ruleset- node to extract the rules and then used a Group Loop to loop through each predicted quality value (4-7) and count the number of times a feature is present in the quality rule set.
This led me to being able to present the results as a -Parallel Coordinates Plot-
As in the solution presented by Aline, the most important feature is the Alcohol content followed by Sulphates. It is apparent that only the first 3/4 features have any importance in determining the Quality of the wine and the other features can be ignored.
You can find my solution on the hub here:
Best wishes
Heather