running some method comparisons, aiming to demonstrate superiority of one parameter set amusingly running into the problem not that the experimental parameters don't improve things, but that the baseline parameterization is implausibly garbage
oh good there are tons and tons of negative weights well that explains that fuck fuck fuck
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Always sanity check your coefficients!
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I'm so used to the ML paradigm at this point that I straight up automatically disbelieve all interpretable coefficients
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ME TOO I can probably ratfuck around it
End of conversation
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