Comments (4)
Hi @AndreaPesce , thanks for your interest in this package. Default model has only simple checks and try to infer the most common use cases. You can provide your multi-class model object (without training) and use LOFO. If you are aware of it and still want to have multi-class in default model, please let me know.
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Hi @aerdem4, thanks for the answer. I'll define the model to be a Classifier.
I think that if I define a classification metric as scoring param, then the model can be for multiclass or binary classification, so the model has to be a classifier. The choice should not depends on the number of unique value, but on the scoring metric.
If there's no need for you to add this option, then I'll close the issue.
Thank you again!
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If the choice depends on the metric, then I have to keep a static list of all metrics, which will need to be updated every time sklearn is updated. Besides LOFO allows you to have your own metric, then it won't be possible to guess for these custom metrics. I also want the default model to understand if it is a multi-class problem but I am looking for the most convenient solution.
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the same as #40
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Related Issues (20)
- How to use GroupKFold? HOT 10
- Add logging or restart mechanism HOT 2
- Sample_weight? HOT 2
- Add the choice between Mean/Std and Median/IQR HOT 5
- Having a lot of features + Using LOFO? HOT 3
- usage question HOT 2
- Groupkfold or Groupshufflesplit Cross Validation HOT 1
- Support multiclass classification ? HOT 2
- TimeSeriesSplit with Lofo HOT 1
- Feature selection using statistical significance
- How to perform feature selection with hyperparameter tuning?
- Returns NaNs all the time HOT 1
- Any tutorial for dealing with genetic data? HOT 2
- Could you add a reference? HOT 1
- Running the example in the readme throws errors
- Compatibility with neural network: replacing with constant value instead of dropping the feature HOT 2
- requirements.txt not packaged in source distribution
- Pandas 2.0.x compatibility HOT 5
- Variable Grouping Only Works When Model Parameter is Kept To Default HOT 5
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