Uploaded Test files

venv/Lib/site-packages/sklearn/metrics/_plot/base.py

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+def _check_classifer_response_method(estimator, response_method):
+    """Return prediction method from the response_method
+
+    Parameters
+    ----------
+    estimator: object
+        Classifier to check
+
+    response_method: {'auto', 'predict_proba', 'decision_function'}
+        Specifies whether to use :term:`predict_proba` or
+        :term:`decision_function` as the target response. If set to 'auto',
+        :term:`predict_proba` is tried first and if it does not exist
+        :term:`decision_function` is tried next.
+
+    Returns
+    -------
+    prediction_method: callable
+        prediction method of estimator
+    """
+
+    if response_method not in ("predict_proba", "decision_function", "auto"):
+        raise ValueError("response_method must be 'predict_proba', "
+                         "'decision_function' or 'auto'")
+
+    error_msg = "response method {} is not defined in {}"
+    if response_method != "auto":
+        prediction_method = getattr(estimator, response_method, None)
+        if prediction_method is None:
+            raise ValueError(error_msg.format(response_method,
+                                              estimator.__class__.__name__))
+    else:
+        predict_proba = getattr(estimator, 'predict_proba', None)
+        decision_function = getattr(estimator, 'decision_function', None)
+        prediction_method = predict_proba or decision_function
+        if prediction_method is None:
+            raise ValueError(error_msg.format(
+                "decision_function or predict_proba",
+                estimator.__class__.__name__))
+
+    return prediction_method