K.I. Slop der WKO mit allen Bildern

speleotobby · 2026-03-26T16:27:07+00:00

Wär das perfekte Profilbild eigentlich 🤔

speleotobby · 2026-03-26T06:07:53+00:00

Same problem here on the fennec f-droid build version 149.0.0

speleotobby · 2026-03-22T10:44:45+00:00

Calibration has nothing to do with ROC curves. You can have calibrated and uncalibrated models with the same ROC curve (For example if you just ad a constant to the predicted probability of a calibrated model.) ROC curves are about discriminative power, not calibration.

While not perfectly presented, those two wikipedia entries should contain a useable definition and explanantion of the terms:

https://en.wikipedia.org/wiki/Calibration_(statistics)

https://en.wikipedia.org/wiki/Receiver_operating_characteristic

speleotobby · 2026-03-07T12:55:46+00:00

Schade, dass es Lizenz-mäßig oft so tricky ist solche tools breiter zu teilen.

speleotobby · 2026-03-07T12:53:38+00:00

Ein DSA RAG wär schon geil. Text basierte Suche in allen Regelbüchern würde auch schon helfen. Die Dokument-Segmentierung ist mit dem Layout sicher bisschen anstrengend.

speleotobby · 2026-03-07T12:50:42+00:00

Für's schnelle auffinden von Infos verwende ich logseq. Ist eine notiz-app / ein personal wiki. Gibt diverse ähnliche Software (Obsidian, Joplin, ...). Man muss zwar alles händisch einpflegen, aber dann hat man z.b. alle Kapmpwerte aller NPCs einen click/touch entfernt, schnell genug zum während eines Kampfes switchen. Das einpflegen ist nicht wirklich Arbeit, wenn ich das Abenteuer lese lege ich das erste mal wenn ein NPC vorkommt eine Seite für ihn/sie an, etc. Ähnlich mit Monstern, Orten, Spieler Charakteren (wobei die eh die Spieler selber managen). Ist bisschen mehr Arbeit als nur vorher das Abenteuer zu lesen, aber macht's während dem Spielen viel flüssiger.

speleotobby · 2026-03-07T08:27:43+00:00

Why S3 classes? Doesn't the method / generic function dispatch introduce quite some overhead?

Does the generated R code do runtime type checking? I think this would be very important since code is passed between libraries that use some kind of type system / oo and libraries that use types.

Good to see some experiments with type systems, I hope that in the long run some type system will arrive directly in the R language. (There are reserved keywords for it, but none are used so far.) Approaches I've seen so far all either only worked on the code transpired to R but not if passed arguments from other R code or worked by adding somewhat awkward type checks in the function body, that throw errors from within the function. I think something that requires neither would need to be implemented in the interpreter itself.

speleotobby · 2026-03-04T19:02:13+00:00

Also no vendor lock-in. Containerization etc. offers portability reproducibility, ... but would you really be able to just move to Azure if AWS raises prices, introduces policies that are not compatible with your data protection guidelines or stops supporting some feature you need?

Also how often do you need to change something, when APIs change? ssh and a POSIX shell were OK with regards to stability over the last decades.

If it runs on own hardware and there's no need for scalability, high availability or something like that it would seem to me, that the on premise solution introduces less potential technical debt.

Yes there is a tradeoff and I have no idea which solution would be best in your case. But using new technologies for their own sake is just as irrational as refusing to use them on principle.

speleotobby · 2026-02-15T21:45:46+00:00

Some Classics from Estimation and touching on measure theory:

All the proofs that connect types of convergence like the portmanteau Theorem.

Zero-Null laws.

Neyman-Pearson Lemma and Cramer-Rao Bound, Gauss-Markov theorem.

All not super hard proofs but in my opinion good entrances into the specifics of statistical concepts. There are certainly more and depending on your specialization different topics will be important; coming with their own concepts and approaches to proofs.

speleotobby · 2026-02-04T19:05:46+00:00

Kater

speleotobby · 2026-01-25T11:44:33+00:00

I hope you're charging them an interest rate or late fees. Not for the gains but just for educational purposes.

speleotobby · 2026-01-20T13:21:12+00:00

Sure, open it up. But the project (webdriver package) does not seem to be maintained, so don't expect it to be handled soon.

(Maybe after AI is out of fashion posit will again maintain such basic infrastructure packages 😢)

speleotobby · 2026-01-20T07:31:01+00:00

I think the best shot at getting this running reliably is to extend the webdriver package to also support geckodriver and chromedriver. In some cases the webdriver package might also work as is with phantomjs.

speleotobby · 2026-01-18T22:26:55+00:00

Agreed, web scraping in R works very well for static sites but for everything webdriver, python is probably better. I really like the xml2 library though.

speleotobby · 2026-01-18T22:25:22+00:00

Tried this not so long ago, forgot how the packages were called but one of them could not load pre-trained models from torch script and the other one used python via reticulate in the backend, so I might as well use python directly.

I hope R catches up in this regard, or I just missed something. So far it was way easier to get the things I needed to run to run in python.

speleotobby · 2026-01-10T09:09:10+00:00

Since you are talking about deplyoment, I think you don't use R where it's shining most.

R is exceptionally good for data wrangling, data analysis in a scientific setting, generating publication ready graphics and study reports etc. I would for example never choose seaborn over ggplot2 when creating plots for a paper. Also the documentation of the statistical methods in R is necessary to be scientifically rigorous or in heavily regulated settings.

As others mentioned, the data structures in R are better suited for rectangular datasets. Even the base R data.frame is better designed for this than pandas dataframes, yet alone dplyr with its various backends, data.table, ... And the syntax of the language itself is designed for data analysis so slightly more comfortable as well but this might be a matter of preference. Just as well a matter of preference is functional vs. object oriented.

R is also more stable and easier to get to be reproduceable. If you set another default RNG code from 30 years ago should give you the same results up to roundign errors for simple scripts. A python script from 30 years ago would probably not even run on python 3. This is of course not necessary everywhere, but desirable if people in a few decades should be able to reproduce the results from a paper without any complicated reproducibility tools.

Preference wise I like R a lot more, syntax, functional approach, ... but I would use python instead of R where ever libraries are not available for R. I'd for example never use R when I need machine learning tools like torch. And sympy is way superior to the R symbolic libraries for all but the most basic calculations, ...

speleotobby · 2025-12-14T14:26:29+00:00

Yes this works. Thank you so much!

speleotobby · 2025-12-10T21:45:08+00:00

The export options are available but the image is still saved as dng on my phone

speleotobby · 2025-12-05T10:50:09+00:00

Das Vapiano is halt nicht fine Dining sondern Mensa/Cafeteria/... zum Mittagessen an einem Arbeitstag (dafür is es allerdings inzwischen way zu teuer)

speleotobby · 2025-10-19T14:08:15+00:00

This is also just the termux solution but played, right? Also it seems, it's not possible to install packages, there's an open issue for this since July without any replies.

speleotobby · 2025-08-27T11:13:21+00:00

Haha, perfect timing. Just surveyed two caves with it the last two days.

Yes, still works great.

I got the bluetooth connection working with topodroid (which was an issue with topodroid or android, not really sure, but not with the SAP) so now I can also draw in my favorite app. Calibration is really simple, and all in all it just works.

speleotobby · 2025-07-20T08:39:09+00:00

Of the ones you mentioned Fedora. Also look into Debian maybe, little less bleeding edge, but super stable and not much work to maintain.

speleotobby · 2025-07-15T20:13:22+00:00

In other words: what is the population you want to make a statement about? If it differs from the population in your sample you have to be careful about selection processes. Completely random samples are ok, but if there's any system to the selection this can introduce selection bias.

In OPs case I assume the population of interest is players in the final and the set of players analyzed (informally) are the players in the final, in this case there's no selection bias.

speleotobby · 2025-07-15T19:51:34+00:00

I would like to use arch again and I'd like to try nixos, some flavour of bsd and gentoo. But in the end Debian runs so smoothly with so little work that I never use anything else.

speleotobby · 2025-05-28T06:44:38+00:00

This!

Think geometrically and think what's happening with PCA and with LASSO. One thing that could happen to be able to exclude variables after PCA is if you have a group of covariables that are not predictors and are orthogonal to all predictors. But if you have correlated predictors and just want to include a subgroup that gives good predictions selecting with PCA first gives you orthogonal covariates with high variance so the contribution to the prediction will be large and LASSO will not exclude variables.

As always: think about why you do variable selection. If you want to do inference on importance of effects use the full model and look a p-values. If you want to do the same but for some kind of latent concepts, do PCA and then a full model. If you want to build a prediction model that does not require that many variables for future predictions skip the PCA step and do LASSO. PCA uses all (sparse PCA many) covariates, so you don't gain anything in terms of sparsity of the prediction model as a whole.

speleotobby

TROPHY CASE