Canonical Flop Subsets
Has anyone invented canonical flop subsets?
We have regular flop subsets [Pio] [GTO+]. They are useful for making "mini aggregate reports". You can take the weighted average of each flop to get something approximating the global average strategy/EV/EQR/etc.
But these are not canonical. They cluster around the average flop, not the different types of flops. For example, if I open the Pio 3-flop subset, you get three unpaired broadway FD flops. Why? Because these are the most common flop types, so they represent the mean of all flops.
- QsJs4h
- As6s5h
- Ks9s8h
What I'm looking for is more like, a representative subset. Something that shows off the different types of textures you'll face. Now I could pretty easily just make up my own set of representative flops for each common texture. But I'm wondering if there's a more rigorous way to do it?
Put another way:
- Aggregate Subset: Minimizes error of average
- Canonical Subset: Maximizes representation of distinct features/textures
