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Having a classifier which differentiates both patterns solves the problem (distance to corners against Walls).

If not, making many k-NN searches with k=1 gives you 30% of the ticks from one pattern and 70% of the ticks from the other pattern, and the resulting pattern is a 30%/70% mix of the two. It assumes a 3rd unseen pattern can be predicted from 2 previous patterns.

Should perform well against orbital movement, where turn rate changes gradually with distance and a 3rd unseen turn rate (or a zig-zag) can be predicted from 2 others. But perform bad against pattern movement, where patterns don't change gradually with classifiers.