Are there plans of implementing a simple feature to ignore outliers in scalar plots?
Here is a plot that is not readable because of outliers. I will usually just use log-scale on the y axis, and that works fine in most cases, but sometimes you do not want to mess with the scale and just automatically zoom in on the 'typical' range of the data.
Hi @<1655744373268156416:profile|StickyShrimp60> , happy to hear you're enjoying ClearML 🙂
To address your points:
Is there any way to lock setting of scalar plots? Especially, I have scalars that are easiest comparable on log scale, but that setting is reverted to default linear scale with any update of the comparison (e.g. adding/removing experiments to the comparison).
I would suggest opening a GitHub feature request for this
Are there plans of implementing a simple feature to ignore outliers in scalar plots?
Can you please elaborate? Screenshots are always welcome 🙂
In the hyperparameter pane of the comparison view I can only see up to 10 experiments. Will more experiments be visible in the paid version or self-hosted version?
I'm afraid not.
Is the hyper-parameter optimization App be available in the self-hosted solution ? (I am thinking about trying out a self-hosted setup on AWS)
It's available only in the PRO and the Scale/Enterprise licenses. However in the self hosted version there is an HPO example - None
Lastly, when preparing reports, is there anyway to include math (e.g. LaTeX mathmode block) ?
I'm not familiar with it, but the reports are based on markdown so anything a markdown editor can do, you can do within the reports.
I see. Sounds like a good idea! Please open a GitHub feature request 🙂
FYI @<1523701070390366208:profile|CostlyOstrich36> after a quick search it seems there is already a request for this 🙂 None