sade_95

3 ms·

1. 1.▲
   by sade_95 3mo ago

   Thanks for the advice; you're absolutely right ,it was just to grab attention.
2. 2.▲
   by sade_95 3mo ago

   Thanks for the epicycles clarification, I did not know each body had its own fitted set. This makes the parallel with overfitting even stronger. And I think we agree on the real problem: a good fit on one problem, made with a universal appr
3. 3.▲
   by sade_95 3mo ago

   This is exactly the niche I had in mind, thank you for the concrete example. Where theory works (small deltas, linear regime) nobody needs my tool. Where turbulence starts, engineers already live with empirical correlations and weird expone
4. 4.▲
   by sade_95 3mo ago

   You are right, and I concede the point. I chose the operators and the parsimony rule knowing already that laws like Kepler exist. So "Kepler took 10 years" is a bit of theater, the honest claim is only: if a short law exists in th
5. 5.▲
   by sade_95 3mo ago

   Funny you ask, I actually spent a weekend on exactly that. Took the SPARC rotation curve data (~2700 points, 150+ galaxies), built the radial acceleration relation from the raw files and let the engine search. Honest result: it recovered a0
6. 6.▲
   by sade_95 3mo ago

   Fair point, and nyrikki has it right: the engine never sees units. Everything is normalized to dimensionless magnitudes before the search, so that formula is an empirical fit on pure numbers, not a physical law. I should say that more clear
7. 7.▲
   by sade_95 3mo ago

   You're right, and I'd go further: the inductive bias isn't incidental, it's the whole product. Short trees over {+, *, sqrt, exp, ...} plus a parsimony penalty is basically Occam's razor made executable. A bias-free
8. 8.▲
   by sade_95 3mo ago

   Thanks for the formatting tip, noted. Isn't e different for each planet? Yes, each planet got its own e (Mercury 0.206, Venus 0.007, Earth 0.017...). The correlation still comes out at 1.00000 because all eccentricities are small while
9. 9.▲
   by sade_95 3mo ago

   Good questions — I ran all three: Semi-minor axis: I added b as a second feature (b = a·sqrt(1−e²), so corr(a,b) = 1.00000 to 5 decimals; Mercury is the only planet where they differ by more than 2%). It still picked a and ignored b complet
10. 10.▲
    by sade_95 3mo ago

    What My Project Does GP_ELITE is a symbolic regression engine in pure Python: given (X, y) data, it searches for a readable mathematical formula linking them, instead of a black-box model. To show what that means concretely: I gave it nothi
11. 11.▲
    Pure-Python symbolic regression that rediscovered Kepler's law from 8 data point(github.com)

    44 points by sade_95 3mo ago|25 comments
12. 12.▲
    My symbolic regression engine rediscovered Kepler's Third Law from raw data(github.com)

    3 points by sade_95 3mo ago|0 comments
13. 13.▲
    by sade_95 3mo ago

    This is an incredibly refreshing piece of work. The decision to use a content-addressed heap over the Leech lattice Lambda_24 canonicalized under the Conway group Co_0 to achieve O(1) structural equality is brilliant, especially for compile