BigBayesian
BigBayesian t1_j6mm8pk wrote
Reply to I (20mtf) went on a very nice date with a guy (19m), who lied to me afterwards. Second chance? by Curious-Wear2947
“I don’t think it was malicious, but WTF!” Sums it up nicely. You can do better. Being alone is better. Encouraging him to seek treatment for his depression wouldn’t be out of line, though.
BigBayesian t1_j23k7xt wrote
Reply to comment by KaTaLy5t_619 in [OC] Defence budgets around the world by giteam
It’d be great if there were some good way to measure corruption and put it into the graph. But I suspect that’d be hard. It might also be divisive - if a US senator holds up a defense appropriations bill until some spending for their district is added, is that corruption? I suspect you can find conflicting, earnest, legitimate answers to that question.
BigBayesian t1_j23jpl8 wrote
Reply to comment by OG_ninnyhammer in [OC] Defence budgets around the world by giteam
That sounds incredibly complicated (like, literally a sizable fraction of the complexity of all US foreign policy), and really divisive (I.e. would all NATO countries count? Would Ukraine? India? Pakistan? Saudi Arabia? Israel? Taiwan?). You can make really good arguments that the answer for any of those is “yes” or “no”. For that reason, I think such an illustration would be difficult to construct, and impossible to treat as data without an agenda.
BigBayesian t1_j23ixzm wrote
Reply to comment by nicat97 in [OC] Defence budgets around the world by giteam
Believe it or not, the US has a military presence outside of it’s immediate geographic neighbors. It also projects force even further than that.
I don’t think Mexico and Canada are at the top of the list of countries that the US spends it’s military budget worrying about. Perhaps it’s border security budget (but even then, maybe not - airport security).
BigBayesian t1_j23im5i wrote
Reply to comment by JuliusErrrrrring in [OC] Defence budgets around the world by giteam
I feel like the “Rich man, poor man” metaphors don’t go that well to argue against this metric, because the next step is “Do you want to be a rich man without a gun surrounded by poor men with guns?”
BigBayesian t1_j23idvn wrote
Reply to comment by Musole in [OC] Defence budgets around the world by giteam
US has about 20% of Africa’s population, and a GDP of $25T compared to $3T for Africa.
BigBayesian t1_jam6z7u wrote
Reply to [D] Are Genetic Algorithms Dead? by TobusFire
Genetic algorithms are good, as you said, when you really understand the space and can come up with a really good candidate generation system. They’re okayish (or, the same as everything else) when you have no understanding of the space at all, and you’re just totally guessing. They can’t latch onto a curve in design space as well as things that look at a simpler gradient can. So maybe they’re best used for really complex spaces where gradient based methods don’t do well. The kind of places you’d use Gibbs sampling, or general optimization algorithms.
So, basically, they’re useful when you have good feature engineering already done, like many methods that have fallen out of vogue in the age of letting algorithms and data do your feature engineering for you. And they’re as good a shot in the dark as any when standard methods fail and you’ve got no clue how to proceed.
So, yeah, the number of times genetic algorithms are the “right” choice is pretty limited these days.