fix

Author: fkiraly

src/hyperactive/integrations/sklearn/_adapter/_sklearnadapter.py

@@ -18,9 +18,6 @@ def _refit(self, X, y=None, **fit_params):
 
     def _check_data(self, X, y):
         X, y = indexable(X, y)
-        if X is not None:
-            if X.ndim == 1:
-                X = X.reshape(-1, 1)
         if hasattr(self, "_validate_data"):
             validate_data = self._validate_data
         else:

src/hyperactive/integrations/sklearn/hyperactive_search_cv.py

@@ -78,23 +78,6 @@ def __init__(
         self.refit = refit
         self.cv = cv
 
-    def _refit(self, X, y=None, **fit_params):
-        self.best_estimator_ = clone(self.estimator).set_params(
-            **clone(self.best_params_, safe=False)
-        )
-
-        self.best_estimator_.fit(X, y, **fit_params)
-        return self
-
-    def _check_data(self, X, y):
-        X, y = indexable(X, y)
-        if hasattr(self, "_validate_data"):
-            validate_data = self._validate_data
-        else:
-            from sklearn.utils.validation import validate_data
-
-        return validate_data(X, y)
-
     @Checks.verify_fit
     def fit(self, X, y, **fit_params):
         """

src/hyperactive/integrations/sklearn/opt_cv.py

@@ -84,23 +84,6 @@ def __init__(
         self.refit = refit
         self.cv = cv
 
-    def _refit(self, X, y=None, **fit_params):
-        self.best_estimator_ = clone(self.estimator).set_params(
-            **clone(self.best_params_, safe=False)
-        )
-
-        self.best_estimator_.fit(X, y, **fit_params)
-        return self
-
-    def _check_data(self, X, y):
-        X, y = indexable(X, y)
-        if hasattr(self, "_validate_data"):
-            validate_data = self._validate_data
-        else:
-            from sklearn.utils.validation import validate_data
-
-        return validate_data(X, y)
-
     @Checks.verify_fit
     def fit(self, X, y, **fit_params):
         """Fit the model.