Set additional parameters in algorithms (parameters which are not tuned)

mljar / mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

https://mljar.com

MIT License

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Set additional parameters in algorithms (parameters which are not tuned) #461

Open jmrichardson opened 3 years ago

jmrichardson commented 3 years ago

Hi, is it possible to send parameters to a specific model? I am currently just using lightgbm and would like to set the following: is_unbalance=True

Thank you

pplonski commented 3 years ago

@jmrichardson there is no such functionality, but I will add it.

jmrichardson commented 3 years ago

Great news! It would also be great to be able to set default parameters per model. I have a pretty unique dataset and the default parameters don't quite work well for initial start. Thank you

pplonski commented 3 years ago

@jmrichardson good idea. Looks that there should be option to set 3 types of parameters:

additional parameters for algorithms (not tuned, just passed to the algorithm)
default parameters for algorithm (that will be used in first model training),
new range of parameters that will be optimized for algorithm

jmrichardson commented 3 years ago

Hi @pplonski , wanted to see if this is on the roadmap and when you think it might be available? Thanks for your consideration.

pplonski commented 3 years ago

Hey @jmrichardson, I will try to add this to the next release. But cant tell when it will be, I started to work on our new product: a notebook with no-code blocks which will make Python coding simple and available for many (the new product will have our AutoML).

jmrichardson commented 3 years ago

Hi, thank you for the fast reply! The new product I am sure will be very useful to the community! There is no rush, especially after testing the Optuna integration which handles most of my needs. Thanks again.

alitirmizi23 commented 2 years ago

Any idea if we can do this now? with automl and having custom parameters per model?

pplonski commented 2 years ago

Hi @alitirmizi23! Currently, all my efforts are focused on the https://github.com/mljar/mercury framework for converting notebooks to web apps. I hope I can built sustainable bussiness around Mercury and use founds to develop MLJAR AutoML.

I do provide commercial support for MLJAR AutoML. I can implement this feature if needed by a commercial client. Licenses start at $1000/year.

The alternative is to implement this yourself or wait - from time to time I have interns that can code this.

alitirmizi23 commented 2 years ago

Hey @pplonski, I understand. Maybe I'll try to implement myself. as far as license goes, we already have another enterprise automl framework. To your credit, i have found MLJAR Supervised to be one of the best open source autoML frameworks available

pplonski commented 1 year ago

@adrianblazeusz could you please take a look at this issue?