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I have a strong feeling that, if people really put an effort into reading and replicating more papers, we would find that a lot of what's being published is simply meaningless. In grad school I had a subletting roommate for a while who was writing code to match some experimental data with a model. He showed me his model. It was quite literally making random combinations of various trigonometric functions, absolute value, logarithms, polynomials, exponents, etc. into equations that were like a whole page long and just wiggling them around. He was convinced that he was on a path to a revolution in understanding the functional form of his (biological) data, and I believe his research PI was onboard. I guess "overfitted" never made it into the curriculum. |
Technically, we call that a "neural network". Or "AI".