You can solve regression problems by storing local patterns and using similarity matching instead of training large global models—this is faster, uses less memory, and works well for scientific data that repeats in certain regions.
This paper proposes a novel regression method inspired by how fruitflies sense their environment. Instead of building complex global models, the approach stores a library of representative local patterns and makes predictions by finding similar patterns to a query and combining their responses.