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It may be simply mathematically impossible to get to 10 percent given the observable variables. Maybe netflix knows this and just gets synthesized research on
by aswanson 18y ago
It may be simply mathematically impossible to get to 10 percent given the observable variables. Maybe netflix knows this and just gets synthesized research on the cheap.
- pg 18y agoI'd guess the machine learning guys by this point understand the data set at least as well as Netflix does.
- aswanson 18y agoWouldn't argue with that, but they may have run up against a bound, multiplied it by a constant, and said to themselves "highly unlikely that anyone can beat this, so lets put it out there and see if someone out there can beat it." So far no one has and they have gotten a ton of research on the cheap, like the current team's for 50 k USD. Smart.
- jderick 18y agoThe machine learning guys have only a subset of the full dataset to work with. They have to send their algorithms to Netflix for testing on the full dataset. So it may be possible Netflix knows something they don't. It does seem quite strange how close and yet how far that 10% mark has been.
- Retric 18y agoBecause they are testing it vs a fixed data set teams can gain information about that data set based on their submissions. Which is why several teams mix and mach several different approaches. They can increase the weight of each approach over time and game the system. Edit: I am not saying they are intentionally cheating rather it's one of the reasons that approach works.
- pg 18y agoHmm. What could Netflix know, though? Is it even possible to quantify how hard it is to improve a recommendation algorithm by a certain amount?
- aswanson 18y agoMaybe there is an inherent noise floor for the optimal estimator for the dataset they have found or bounded.
- Eliezer 18y agoThey're over 9% already. Sheesh.
- Haskell 18y agoIf the goal had been 5%, you would say: - It may be simply mathematically impossible to get to 5 percent... And they are already at 9.56%.
- aswanson 18y agoNo I wouldn't have, because I could only make a statement like that after seeing performance information. Since at least 40 teams beat that performance the first year, I would have said they set the bar too low.
- deleted 18y ago[deleted]
- Haskell 18y agoAnd why do you think 10% is impossible but 9.5% is not?
- aswanson 18y agoI said they may have found a bound. I didn't say it was; it said there may be a limit. Re-read the ancestor.
- Haskell 18y agoYou are playing with words. The point is that there's really not much difference between 10% and 9.56%. Netflix's Grand Prize could very well had been 9.64% and it would already had been won, despite everybody saying one year ago that 9.64% might be impossible given the dataset. We will talk again in one year to see if 10% may be impossible.
- Haskell 18y agoOps... substitute 9.64% by 9.56% in that comment. :)
- 18y ago
- wheels 18y agoThey are getting it on the cheap. They've got many teams of top-notch folks working on building an algorithm tailored for their data-set and problem definition. For what they're getting out of this, $1m is a stupidly low price. If they've incorporated the stuff that's come out so far, they've already boosted their sales by several million based on the results of the contest.