I have some questions regarding mubu.knn and scaling, related with each other: basically, how are the axes normalized with respect to each other in the multidimensional space? I bet it depends on scaling, but as far as I understand, scaling only concerns the scaling of the input values, not of the corpus itself.
Let me try to be more clear: Let’s say for instance, a matrix consists of two columns, frequency (between 0 and 20000 Hz), and level (between -90 dB and 0 dB). If scaling is set to “off”, does it mean that axes are not normalized (which would mean, frequency has much more weight than level)?
And: if the axes of the corpus are indeed normalized with respect to each other (either with max-min or with std), is the input scaled accordingly?
Or (second hypothesis), the axes are always normalized (for instance with std), but then, what’s the function of the “scaling” argument? I mean, I’d like to compare frequencies with frequencies and levels with levels (and not with normalized frequencies and levels).
Last question: if I want to simulate the “radius” mode from catart, I guess I should set the “k” argument to a very high value, then set the radius, and then take one of the outputs randomly, correct?