cross_validation fit_transform removed

Author: vm-aifluence-jro

qolmat/benchmark/comparator.py

@@ -121,9 +121,10 @@ def evaluate_errors_sample(
                     hole_generator=self.generator_holes,
                     n_calls=self.n_calls_opt,
                 )
-                df_imputed = cv.fit_transform(df_corrupted)
+                imputer.hyperparams_optim = cv.optimize_hyperparams(df_corrupted)
             else:
-                df_imputed = imputer.fit_transform(df_corrupted)
+                imputer.hyperparams_optim = {}
+            df_imputed = imputer.fit_transform(df_corrupted)
             subset = self.generator_holes.subset
             errors = self.get_errors(df_origin[subset], df_imputed[subset], df_mask[subset])
             list_errors.append(errors)

qolmat/benchmark/cross_validation.py

@@ -207,7 +207,7 @@ def obj_func(**hyperparams_flat):
 
         return obj_func
 
-    def optimize_hyperparams(self, df: pd.DataFrame) -> Dict[str, Union[float, int, str]]:
+    def optimize_hyperparams(self, df: pd.DataFrame) -> Dict[str, Any]:
         """Optimize hyperparamaters
 
         Parameters
@@ -217,7 +217,7 @@ def optimize_hyperparams(self, df: pd.DataFrame) -> Dict[str, Union[float, int,
 
         Returns
         -------
-        Dict[str, Union[float,int, str]]
+        Dict[str, Any]
             hyperparameters optimize flat
         """
         list_spaces = get_search_space(self.dict_config_opti_imputer)
@@ -231,25 +231,5 @@ def optimize_hyperparams(self, df: pd.DataFrame) -> Dict[str, Union[float, int,
         )
 
         hyperparams_flat = {space.name: val for space, val in zip(list_spaces, res["x"])}
-        return hyperparams_flat
-
-    def fit_transform(self, df: pd.DataFrame) -> pd.DataFrame:
-        """
-        Fit and transform estimator and impute the missing values.
-
-        Parameters
-        ----------
-        df : pd.DataFrame
-            dataframe to impute
-
-        Returns
-        -------
-        pd.DataFrame
-            imputed dataframe
-        """
-
-        hyperparams_flat = self.optimize_hyperparams(df)
-        self.imputer.hyperparams_optim = deflat_hyperparams(hyperparams_flat)
-        df_imputed = self.imputer.fit_transform(df)
-
-        return df_imputed
+        hyperparams = deflat_hyperparams(hyperparams_flat)
+        return hyperparams

qolmat/imputations/imputers.py

@@ -48,8 +48,6 @@ def __init__(
         random_state: Union[None, int, np.random.RandomState] = None,
     ):
         self.hyperparams_user = hyperparams
-        self.hyperparams_optim: Dict = {}
-        self.hyperparams_local: Dict = {}
         self.groups = groups
         self.columnwise = columnwise
         self.shrink = shrink