Johannes P. Dürholt

Hi JD, thanks for pointing this out. We are planning to add active learning acqfs soon. I need to think a bit more about the MO case ;) I just...

This are great news, I indeed started last week a branch to implement an `ActiveLearningStrategy`, which is not yet finished. I will clean this up and document it a bit...

Good point, I have it already for a longer time on my bucket list, from the `botorch` side, this is already prepared: https://github.com/pytorch/botorch/blob/68fbb68d4a78efd2b803071d883081b2c45a70ae/botorch/models/transforms/input.py#L878 The question is how to set it...

Furthermore, the question would be if the log transformed inputs should then also undergo normalization/standardization and how to set this up in a flexible way.

https://ax.dev/docs/models.html#transforms This describes how it is done in Ax, which differs a bit from our current approach.

Hi @Osburg, as a starting point for the discussion, here is an MWE to reproduce the behavior: ```python from bofire.data_models.features.api import ContinuousInput from bofire.data_models.constraints.api import LinearEqualityConstraint, LinearInequalityConstraint, NChooseKConstraint from bofire.data_models.domain.api...

Hi @Osburg, I did some reverse engineering on how Minitab is doing it, they are actually scaling between -1 and 1, I think we should also give this option at...

Closed with https://github.com/experimental-design/bofire/pull/358.

You could take the candidates after their generation and and fed them into the `strategy.calc_acquisition` method, then you will return the actual acqf values. https://github.com/experimental-design/bofire/blob/591401c0db8963b116b3c8193e11c2e49b88738a/bofire/strategies/predictives/botorch.py#L160 Regarding your second question: I...

Nothing to apologize! Regarding your questions: 1. Did you use the Permutation Feature Importance feature? Currently it runs only over orginal features and not the transformed ones. In principal, it...