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Hi,
I'm trying to tune lightgbm for a regression problem and need to use groupKFold for cross-validation.
By default, automl.fit() takes repeatedkfold as split_type. I looked up at the [documenta…
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sklearn f1_score makes use of 'binary' as average default parameter. It means, if the problem is a multiclass ones, it must be changed the average parameter to ones of ['micro', 'macro', 'weighted', '…
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I would like to define & use a custom evaluation metric.
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Currently, the model training logs are written into a log file. Instead of writing into a logfile, is there a way to log parameters, metrics using mlflow
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line 394 of flaml/model.py, The train() method does not accept weight as legitimate argument.
Instead, the weight should be specified in line 390 when creating dtrain.
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Is there a way to handle imbalanced datasets in the automl?
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Hi:
Our team has explored the ensemble option in the fit function of automl and got a few errors:
1. There is an error when using both the GLM (LRL1/LRL2) and MLs for the ensemble. For example:
…
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If I leave out X_val and y_val, automl works fine. But if I specify these values, it crashes with the following error:
```python
----> 7 automl.fit(X_train= xtrain,y_train=ytrain,X_val=xvalid,y_va…
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Hi,
While training the learner, a console output is generated, which can take up huge space in the notebook if the time_budget is made large. If I wish to suppress the console output while training…
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Hi:
get_output_from_log returns empty objects for me with no error message:
from flaml.data import get_output_from_log
get_output_from_log(filename = 'test.log', time_budget = 600)
([], [], …