tutorial draft on curse of dimensionality
From the post:
Curse of dimensionality is a widely heard of, largely misunderstood concept in machine learning. There is one single explanation of it circulating, but there is more to it. I will explain what is the curse, and how it complicates everything.
I don’t follow hockey but the example would be easy enough to adapt by subject domain.
The author illustrates one problem with dimensionality and promises to discuss others.
I say “the author” because this is one of those blogs where identification of the author isn’t clear. In academic discussions that is more than a little annoying.
Good illustration of the problem and points for that.