If you are interested in that you could check out the preparation section of my machine learning collection. About tools like vtreat (vtreat for KNIME! – Win Vector LLC) for example. Also the relevant KNIME workflow (Techniques for Dimensionality Reduction – KNIME Community Hub) which has a section about t-sne but I do not know if the methods are being stored in a way to reproduce them. The linked paper goes to a broken page …
Also there is a (quite complete) set called “the poor man’s ML Ops” that I have built (s_601 - Sparkling predictions and encoded labels - "the poor man's ML Ops" (on a Big Data System) – KNIME Community Hub) and sort of explained in a video (in german), slides in english: H2O.ai AutoML in KNIME for classification problems - #11 by mlauber71. This is specific to a big data environment but the priciples would apply. If you can do it on a laptop or small server vtreat or something similar might be more powerful.
About dimension reduction there is also featuretools which I plan on building a KNIME workflow around for some time now …