Library

The library for building a decision tree consists of just two functions: avy-subdiv and avy-tree.

avy-subdiv

The first function, avy-subdiv, tries to split a number in terms of the base in a way that the most leaves have the lowest level:

(avy-subdiv 42 5)
;;=> (5 5 5 5 22)

(avy-subdiv 42 4)
;;=> (4 6 16 16)

(avy-subdiv 42 3)
;;=> (9 9 24)

(avy-subdiv 42 2)
;;=> (16 26)

The returned list of numbers is the candidates distribution per branch.

avy-tree

And here's an example of what avy-tree produces:

(avy-tree
 '("Acid green" "Aero blue" "Almond" "Amaranth"
   "Amber" "Amethyst" "Apple green" "Aqua"
   "Aquamarine" "Auburn" "Aureolin" "Azure"
   "Beige" "Black" "Bronze" "Blue" "Burgundy" "Candy apple red")
 '(1 2 3 4))
;;=>
((1 (1 leaf . "Acid green")
    (2 leaf . "Aero blue")
    (3 leaf . "Almond")
    (4 leaf . "Amaranth"))
 (2 (1 leaf . "Amber")
    (2 leaf . "Amethyst")
    (3 leaf . "Apple green")
    (4 leaf . "Aqua"))
 (3 (1 leaf . "Aquamarine")
    (2 leaf . "Auburn")
    (3 leaf . "Aureolin")
    (4 leaf . "Azure"))
 (4 (1 leaf . "Beige")
    (2 leaf . "Black")
    (3 leaf . "Bronze")
    (4 (1 leaf . "Blue")
       (2 leaf . "Burgundy")
       (3 leaf . "Candy apple red"))))

I think the library turned out to be pretty clean, since it knows nothing of points, buffers or overlays, and imposes no restrictions on the type of leaf items and keys.