Add get_feature_importance() method to AutoML class#825
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When PreprocessingMissingValues._fit_na_fill is called on a column containing exclusively null values, x.value_counts() returns an empty Series. The subsequent sorted(...)[0] then raises: IndexError: list index out of range This adds an early return of None for the empty case, allowing the caller to proceed with a safe fallback fill value. Fixes mljar#770
Adds a unified public method to retrieve global feature importance
computed across all trained models, as requested by the maintainer.
Usage:
automl = AutoML()
automl.fit(X_train, y_train)
importance_df = automl.get_feature_importance()
# Returns DataFrame with columns: feature, mean_rank, models_present
The method returns None when importance data is not available and
raises AutoMLException if fit() hasn't been called yet.
Closes mljar#809
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Description
Closes #809 (filed by maintainer @pplonski)
Adds a convenient
get_feature_importance()method to the publicAutoMLAPI so users can retrieve global feature importance without manually accessing internal model directories.Usage
Design
_compute_global_feature_importance()function used by the structured report — no duplicated logic.pandas.DataFramesorted by importance.Nonegracefully when importance data is unavailable.AutoMLExceptionwith a clear message iffit()has not been called.Changes
supervised/automl.py— 37 lines added (+1 import, +36 method body)