How to save the name of a feature when saving model feature importance
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- Python
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Description
hello
I use the following code
with R.start(experiment_name=EXP_NAME):
mlflow.lightgbm.autolog()
R.log_params(**flatten_dict(model._params))
model.fit(dataset=ds)
Feature importance is saved
But the saved name is Column_XX
What I want saved is the factor name, such as ROC5
I know it can be obtained via
ds.handler.get_feature_config()
But I want to automatically record the original name.
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Research direction
Start by tracing the interaction between mlflow.lightgbm.autolog(), model.fit(dataset=ds), and ds.handler.get_feature_config(). Determine where feature importance is recorded and how the original factor names can be made available; done means saved feature importance uses names such as ROC5 instead of Column_XX.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 32/100