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How to activate hill_climbing when mode='Perform' #314

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RafaD5 opened this issue Feb 16, 2021 · 5 comments
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How to activate hill_climbing when mode='Perform' #314

RafaD5 opened this issue Feb 16, 2021 · 5 comments
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@RafaD5
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RafaD5 commented Feb 16, 2021

Hi! I have run the AutoML class with two different datasets with mode="Perform" but I always get:

Skip hill_climbing_1 because no parameters were generated.
Skip hill_climbing_2 because no parameters were generated.

I tried changing some parameters like top_models_to_improve and hill_climbing_steps but it still didn't work.
When I use mode="Compete" the hill_climbing steps do execute.

How can I get the hill_climbing steps to run in Perform mode?

@pplonski
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Do you have enough time for training? Is the total_time_limit the same as in Compete?

@RafaD5
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RafaD5 commented Feb 16, 2021

Yes, it's the same time.
In one case I used total_time_limit=60*60*16 with mode='Perform' and it only run for about 7 hours and still gave me the message:

Skip hill_climbing_1 because no parameters were generated.
Skip hill_climbing_2 because no parameters were generated.

@pplonski pplonski self-assigned this Feb 16, 2021
@pplonski pplonski added the bug Something isn't working label Feb 16, 2021
@pplonski pplonski added this to the 0.9.0 milestone Feb 16, 2021
@pplonski
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Looks like a bug in Perform mode. Thank you for reporting.

BTW, @RafaD5 do you get good models with MLJAR?

@pplonski pplonski added this to In progress in mljar-supervised Feb 17, 2021
pplonski added a commit that referenced this issue Feb 17, 2021
@pplonski pplonski moved this from In progress to Done in mljar-supervised Feb 17, 2021
@pplonski
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OK, I found the reason. The hill-climbing algorithm was crushing for the Linear algorithm because it hasn't any parameters to be tuned. It is fixed now. Changes are pushed to the dev branch. They will go to the 0.9.0 version.

@RafaD5
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RafaD5 commented Feb 17, 2021

@pplonski thank you for being so quick with the fixes!
I'm happy with the models so far. I've been using the library for 5 days so I'm still exploring and understanding it.
One thing I like a lot is that the library is very transparent. It's easy to know wich models are being trained, where they are saved and what's happening at every step of the training.

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