Merge pull request #1238 from mindsdb/feature/bump_sk_pkgs

Bumped `sktime` to >=0.30.0 and `scikit-learn` to >=1.5.0

Author: ZoranPandovski

lightwood/analysis/nc/calibrate.py

@@ -59,7 +59,7 @@ def analyze(self, info: Dict[str, object], **kwargs) -> Dict[str, object]:
                 all_classes = np.array([ns.encoded_val_data.encoders[ns.target].rev_map[idx] for idx in class_keys])
 
             if data_type != dtype.tags:
-                enc = OneHotEncoder(sparse=False, handle_unknown='ignore')
+                enc = OneHotEncoder(sparse_output=False, handle_unknown='ignore')
                 enc.fit(all_classes.reshape(-1, 1))
                 output['label_encoders'] = enc  # needed to repr cat labels inside nonconformist
             else:

lightwood/encoder/helpers.py

@@ -45,7 +45,7 @@ class CatNormalizer:
     def __init__(self, encoder_class='one_hot'):
         self.encoder_class = encoder_class
         if encoder_class == 'one_hot':
-            self.scaler = OneHotEncoder(sparse=False, handle_unknown='ignore')
+            self.scaler = OneHotEncoder(sparse_output=False, handle_unknown='ignore')
         else:
             self.scaler = OrdinalEncoder()