Make classifiers and regressors clonable

miplearn/classifiers/__init__.py

@@ -6,6 +6,7 @@ from abc import ABC, abstractmethod
 from typing import Optional, Any, cast
 
 import numpy as np
+import sklearn
 
 
 class Classifier(ABC):
@@ -77,6 +78,13 @@ class Classifier(ABC):
         )
         return np.ndarray([])
 
+    @abstractmethod
+    def clone(self) -> "Classifier":
+        """
+        Returns an unfitted copy of this classifier with the same hyperparameters.
+        """
+        pass
+
 
 class Regressor(ABC):
     """
@@ -136,6 +144,13 @@ class Regressor(ABC):
         assert n_inputs_x == self.n_inputs
         return np.ndarray([])
 
+    @abstractmethod
+    def clone(self) -> "Regressor":
+        """
+        Returns an unfitted copy of this regressor with the same hyperparameters.
+        """
+        pass
+
 
 class ScikitLearnClassifier(Classifier):
     """
@@ -185,3 +200,8 @@ class ScikitLearnClassifier(Classifier):
             assert isinstance(sklearn_proba, np.ndarray)
             assert sklearn_proba.shape == (n_samples, 2)
             return sklearn_proba
+
+    def clone(self) -> "ScikitLearnClassifier":
+        return ScikitLearnClassifier(
+            clf=sklearn.base.clone(self.inner_clf),
+        )