Google colab - Feature selection not working about mljar-supervised HOT 7 OPEN

thanks @AlizeeL for reporting, it looks like a bug.

May I ask why are you using Colab? do you need a lot of computational power?

from mljar-supervised.

Some of the datasets I am using can be quite big so yes. Using Colab is a side of my research on accessibility to such tools to non-expert users.

from mljar-supervised.

@AlizeeL thanks for response, we are working on notebook with UI for code generation, that is designed for non-experts users. It is called MLJAR Studio, available as desktop app on our website https://mljar.com/ It is in early development phase, but csv data loading and AutoML training is working. I hope you will find it interesting.

from mljar-supervised.

Thanks @pplonski , it does look promising.

Do you know if my type of issue might get solved in the near future? I just need to know in case I have to work on a machine instead of Colab.

from mljar-supervised.

Thank you. I'm adding @Bocianski to disscussion about plans for fix. For sure, it will help us a lot, if you could provide full code and data for reproduction.

from mljar-supervised.

Here's my code. There's a link at the top to a dataset.
It's a reduced version of my dataset to avoid long computational time. It doesn't change the issues/output.

Let me know if there's any problems with the links, I can send code/data by email if that's the case.
Thanks :)

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i am seeing a similar error while running MLJar on an azure VM, do y'all know why this may be happening?

this is the specific error
"log_loss_eps() got an unexpected keyword argument 'response_method'
Problem during computing permutation importance. Skipping ..."

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