fix Gale-Shapley bug

CHANGELOG.md

@@ -5,6 +5,11 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased] 
+
+### Fixed
+- Add relevance_params in GaleShapleyFeatureSelectionTransform ([#410](https://github.com/tinkoff-ai/etna/pull/410))
+
 ## [1.5.0] - 2021-12-24
 ### Added
 - Holiday Transform ([#359](https://github.com/tinkoff-ai/etna/pull/359))

etna/transforms/gale_shapley.py

@@ -221,7 +221,7 @@ def __call__(self) -> Dict[str, str]:
 class GaleShapleyFeatureSelectionTransform(BaseFeatureSelectionTransform):
     """GaleShapleyFeatureSelectionTransform provides feature filtering with Gale-Shapley matching algo according to relevance table."""
 
-    def __init__(self, relevance_table: RelevanceTable, top_k: int, use_rank: bool = False):
+    def __init__(self, relevance_table: RelevanceTable, top_k: int, use_rank: bool = False, **relevance_params):
         """Init GaleShapleyFeatureSelectionTransform.
 
         Parameters
@@ -238,12 +238,15 @@ class to build relevance table
         self.top_k = top_k
         self.use_rank = use_rank
         self.greater_is_better = False if use_rank else relevance_table.greater_is_better
+        self.relevance_params = relevance_params
 
     def _compute_relevance_table(self, df: pd.DataFrame, regressors: List[str]) -> pd.DataFrame:
         """Compute relevance table with given data."""
         targets_df = df.loc[:, pd.IndexSlice[:, "target"]]
         regressors_df = df.loc[:, pd.IndexSlice[:, regressors]]
-        table = self.relevance_table(df=targets_df, df_exog=regressors_df, return_ranks=self.use_rank)
+        table = self.relevance_table(
+            df=targets_df, df_exog=regressors_df, return_ranks=self.use_rank, **self.relevance_params
+        )
         return table
 
     @staticmethod

tests/test_transforms/test_gale_shapley.py

@@ -4,7 +4,9 @@
 import numpy as np
 import pandas as pd
 import pytest
+from sklearn.ensemble import RandomForestRegressor
 
+from etna.analysis.feature_relevance import ModelRelevanceTable
 from etna.analysis.feature_relevance import StatisticsRelevanceTable
 from etna.datasets import TSDataset
 from etna.datasets import generate_ar_df
@@ -585,6 +587,16 @@ def test_gale_shapley_transform_fit_transform(ts_with_large_regressors_number: T
     }
 
 
+@pytest.mark.parametrize("use_rank", (True, False))
+@pytest.mark.parametrize("top_k", (2, 3, 5, 6, 7))
+def test_gale_shapley_transform_fit_model_based(ts_with_large_regressors_number: TSDataset, top_k: int, use_rank: bool):
+    df = ts_with_large_regressors_number.df
+    transform = GaleShapleyFeatureSelectionTransform(
+        relevance_table=ModelRelevanceTable(), top_k=top_k, use_rank=use_rank, model=RandomForestRegressor()
+    )
+    transform.fit(df=df)
+
+
 @pytest.mark.xfail
 def test_fit_transform_with_nans(regressor_exog_weekend):
     transform = GaleShapleyFeatureSelectionTransform(