More on 'give up theory' in science: Really kickass paper on predictive analytics of personality by Mõttus, @timothycbates, @DMCpersonality, Mroczek @WilliamRevelle.
https://psyarxiv.com/4q9gv/ pic.twitter.com/1EbzsGj0Nn
-
They should give something like a random forests a shot on the raw multinomial/one-hot encoded responses: https://www.reddit.com/r/gwern/comments/9vy62y/your_personality_data_can_do_more_items_provide/e9g0nyz/ … I bet there's some more predictive power to squeeze out, and would demonstrate the point much more dramatically.
RF type stuff didn't produce any more validity for the cognitive tests, was slightly worse than ridge regression, and >10x slower to fit. But for personality, one would have a stronger prior for interaction effects, whereas not for cognitive data.
-
-
Hm, maybe not enough data then. Just for the NEO-PI-R here, unfolding Likert items without facets/Big Fives would give 1200 variables to search over.
-
Throw some xgboost at it and I bet you get some nice results.
-
If RF doesn't pick up anything beyond a dumb linear regression, I'd expect XGboost to likewise add only a little. They're not that different, after all, and if there's not enough data, there's not enough data.
End of conversation
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.