I updated from the official Anki version to beta 4. I’ve scrolled through the forum for a few hours, but there’s too many changes, so I’ll ask here instead: Is there a way to turn off load balancer? Is it fine to optimize straight after updating to 24.10 beta 4? The parameter numbers changed signi…

All I can say is that the minimum retention also went up for all my decks with newly optimized parameters, but in my case it seems to make sense. That being said, 7% sounds like a relatively poor fit. I found that you can often get better parameters using the optimizer tool in the FSRS repository. …

Given that the v4.5 parameters are often not optimal for v5, combined with the fact that it’s not guaranteed that you’ll find the global minimum when optimizing, it makes sense that you can end up with a higher RSME after optimizing for v5, even if the v5 global minimum is better than the v4.5 globa…

Running the optimizer with N different seeds would mitigate the problem and improve accuracy, but it would make it N times slower, so it’s unlikely to be implemented.

Though I should add that if you optimize frequently, you’ll eventually get better parameters just by chance.

I made a simple analysis: [image] [image] [image] [image]

Ok, so 50/50 chance I’d say, no apparent bias? So that would mean that it’s a matter of either just optimizing frequently and hope that you settle into a more optimal set of parameters over time, or use a random seed every time the optimize button is pressed to make it possible to find it by pressin…

Or based on the number of reviews, so that the seed only changes when new reviews have been done. That makes it unnoticeable to end users. The question is if it makes sense statistically speaking. If it increases the chance of getting good parameters in a shorter amount of time.

Or based on the number of reviews, so that the seed only changes when new reviews have been done. That’s an interesting idea. @L.M.Sherlock , what do you think? EDIT: I think using the number of reviews as seed will be strictly better than the current implementation. It will increase the chance…

[image] Expertium: To users, it will look like FSRS got better at utilizing new review data without any drawbacks. Is it real?

My gut feeling is that if you use the same seed and only add a small amount of reviews, the chances are slim that you’ll end up with significantly better parameters. With another seed it might bump you into a more optimal minimum. So I agree with @Expertium , but I can’t prove it statistically. Eithe…

What do you mean? I was trying to say that if the seed changes after every review, it will increase the chances of finding better parameters every time the user does at least 1 review. To the user it will look like he is getting “FSRS parameters currently appear to be optimal” less frequently.

Anticipated Features in 24.10

Anki Help

DerIshmaelite October 27, 2024, 1:20pm 41

I dont know if this is related to this topic, but just a heads up.

Topic		Replies	Views
FSRS 5: Optimizer FSRS	33	1275	November 7, 2024
Measures to prevent new FSRS parameters from being worse than the old ones Suggestions	28	2980	January 28, 2024
Anki 24.04 beta/RC Beta Testing	146	5921	April 1, 2024
Anki 23.10 Beta 1-4 Beta Testing	205	10778	October 18, 2023
25.02 possible bug - minimum recommended retention 0.70 FSRS	19	587	February 27, 2025

Anticipated Features in 24.10

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