71–80 of 197 posts
Has anyone cheated at Kaggle/similar using that approach?
Never understood Kaggle. The Netflix Prize was great. Now it’s just people gaming Kaggle to get a job.
The Netflix Prize was interesting, and drew a lot of attention to it, but ultimately wasn't that simply stuffed into the trash bin? Not long after that, Netflix basically abandoned both user ratings of significance, and realistic recommendations. Now it's just a nonsense engine with some sort of meaningless overlap or whatever they call it.
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There is and it's very effective ... A company I worked in briefly used to have this badge system to honor people that go the extra mile at work, and people were very keen on getting those even though it didn't have any financial compensation behind it
Um that is kindof missing the point. A badge is nothing more than a number expressed in symbols, so you demonstrated just another variation of how to hijack the brain, even if you just read an article showing it to you with numbers... If "improving individual performance" means to you that you perform better at your job, you are already lost.
I'm not going to defend Pleskov but organizers shouldn't have put out the competition with money attached that can simply be solved by scraping data. Good ML competition in fact should even invite cheats because the end goal is not ML for the sake of ML but rather cracking the prediction problem by whatever shortest path possible.
"Winning" by anything that can reasonably called cheating, as in this case, does not advance the general state of the art. Innovation is best served through appropriate rules and competition structure.
One test a good of ML competition: Can it be solved by simply hiring lots of humans to make predictions without incurring significantly more costs than the prize money?
They would have able to win and get away with it if they incorporated the knowledge of the external dataset directly into the ML model, provided they had a reasonable estimate on the fraction of overlap between the external data and the test set. A weak version of this would be to just train on the external data in addition to the provided data. A stronger version would train regularly on the provided training data a…
Of course, we're all human, and he's come clean, but his actions potentially had a negative effect on the non-profit and the animals it places; and competing talents were denied their rightful places.
This comment isn't about condemning him or anything, just let's be honest about what happened here; it wasn't ok, or just system-gaming caught out.
> The goal was to create an algorithm that could predict how quickly a pet would be adopted based on its profile details, from its photo to its breed, sex, size, age, and whether it had been vaccinated or not. > These predictions would be used to optimize and tweak future critters' profiles so that they are adopted as soon as possible. Sorry but, how is this useful? You can't just change the age of an animal to make…
A limited number of parameters can be genuinely altered - a better photo can be taken, and vaccinations can be administered for example.
Animal rehoming centres have to balance throughput with cost; reduced per pet costs mean that they are able to expand or support more complex cases.
Whilst keeping a pet in a "space" and feeding it does cost, this cost can easily be significantly less than vaccinating, particularly as some vaccines require a few days hold post vaccine. Similarly if the vaccine will not alter a pets rehoming chance, then it is an unnecessary cost.
Pictures may be more easily applied as a tighter feedback loop (of the 5, use the 3rd) however they may also indicate other issues that could be addressed (over / underweight, coat damage, etc.) and addressing those issues have costs to balance and predict.
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You can use this to select which pets to put on a platform. For instance, no-kill shelters have to decide which animals they intake since they have finite room. They can save more animals if they pick animals that are likely to be adopted quickly. Obviously, kill shelters have a similar calculus when deciding which animals to cull (and indeed, animals that don't fit in the no-kill shelter go to the kill shelter). I'm…
I'm pretty sure so-called no-kill shelters don't outsource their killing by simply refusing less adoptable animals. And if this contest were advertised as "help us decide which animals to kill first" it probably wouldn't gain traction. This contest sounds ridiculous. It sounds like an attempt to get in on that AI gravy but do so with some sort of feel-good element. Only there is no feel good to it, and the basic prem…