Hi, is there any rule when to normalize data for predictions in KNIME? should it be always for better results?
The rules for normalizing data in KNIME are the normal rules as everywhere in data science: Algorithms like k-means (when it just uses Euclidean distance on the input data) are sensitive to normalization (as it says in the Node Description), while others like a Decision Tree are not affected by it.
Hi Ferry, thanks for answer. is there any systemtic list of where to use and where not need to use normalization? Regards
I wasn’t able to find one extensive enough to reference it here, but you can find a couple of short lists on Google. Alternatively you can look up the algorithms as you use them.