fixup! Fix validate_data usage for new sklearn

Author: janoPig

HROCH/classifier.py

@@ -288,8 +288,10 @@ def predict_proba(self, X, id=None, check_input=True):
         proba = numpy.vstack([1 - preds, preds]).T
         return proba
 
-    def _more_tags(self):
-        return {'binary_only': True}
+    def __sklearn_tags__(self):
+        tags = super(ClassifierMixin, self).__sklearn_tags__()
+        tags.binary_only = True
+        return tags
 
 class SymbolicClassifier(OneVsRestClassifier):
     """
@@ -356,3 +358,6 @@ def predict_proba(self, X):
             classes corresponds to that in the attribute :term:`classes_`.
         """
         return super().predict_proba(X)
+    
+    def __sklearn_tags__(self):
+        return super(OneVsRestClassifier, self).__sklearn_tags__()

HROCH/fuzzy.py

@@ -281,6 +281,12 @@ def _more_tags(self):
             'binary_only': True,
             'poor_score':True, # tests from check_estimator dont have fuzzy number type
             }
+    
+    def __sklearn_tags__(self):
+        tags = super(ClassifierMixin, self).__sklearn_tags__()
+        tags.binary_only = True
+        tags.poor_score = True
+        return tags
 
 
 class FuzzyClassifier(OneVsRestClassifier):
@@ -349,7 +355,7 @@ def predict_proba(self, X):
         """
         return super().predict_proba(X)
 
-    def _more_tags(self):
-        return {
-            'poor_score':True, # tests from check_estimator dont have fuzzy number type
-            }
+    def __sklearn_tags__(self):
+        tags = super(OneVsRestClassifier, self).__sklearn_tags__()
+        tags.poor_score = True
+        return tags

HROCH/hroch.py

@@ -1022,3 +1022,6 @@ def __getstate__(self):
                 all_attributes['models_'] = self.get_models()
         all_attributes.pop('handle_', None)
         return all_attributes
+    
+    def __sklearn_tags__(self):
+        return super().__sklearn_tags__()

HROCH/regressor.py

@@ -224,3 +224,6 @@ def predict(self, X, id=None, check_input=True, use_parsed_model=True):
             The predicted values.
         """
         return super(SymbolicRegressor, self).predict(X, id=id, check_input=check_input, use_parsed_model=use_parsed_model)
+    
+    def __sklearn_tags__(self):
+        return super(RegressorMixin, self).__sklearn_tags__()

setup.py

@@ -121,5 +121,9 @@
     packages=['HROCH'],
     license='MIT',
     include_package_data=True,
-    install_requires=['numpy', 'scikit-learn', 'scipy'],
+    install_requires=[
+    "numpy>=1.19.5",
+    'scikit-learn>=1.6.0',
+    "scipy>=1.6.0",
+    ],
 )