UPD: change name of crf score class

scikit-learn-contrib · Jul 19, 2023 · ec7eab2 · ec7eab2
1 parent b27c567
commit ec7eab2
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Showing 5 changed files with 17 additions and 19 deletions.
diff --git a/mapie/conformity_scores/__init__.py b/mapie/conformity_scores/__init__.py
@@ -1,11 +1,11 @@
 from .conformity_scores import ConformityScore
 from .residual_conformity_scores import (AbsoluteConformityScore,
                                          GammaConformityScore,
-                                         FittedResidualNormalisingScore)
+                                         ConformalResidualFittingScore)
 
 __all__ = [
     "ConformityScore",
     "AbsoluteConformityScore",
     "GammaConformityScore",
-    "FittedResidualNormalisingScore"
+    "ConformalResidualFittingScore"
 ]
diff --git a/mapie/conformity_scores/residual_conformity_scores.py b/mapie/conformity_scores/residual_conformity_scores.py
@@ -143,11 +143,9 @@ def get_estimation_distribution(
         return np.multiply(y_pred, np.add(1, conformity_scores))
 
 
-class FittedResidualNormalisingScore(ConformityScore):
-    # or ConformalResiudalFittingScore
-    # or NormalizedScore
+class ConformalResidualFittingScore(ConformityScore):
     """
-    FittedResidualNormalisingScore (also called CRF) score.
+    ConformalResidualFittingScore (CRF) score.
 
     The signed conformity score = (y - y_pred) / r_pred. r_pred being the
     predicted residual (|y - y_pred|) of the base estimator.

diff --git a/mapie/regression/regression.py b/mapie/regression/regression.py
@@ -13,7 +13,7 @@
 
 from mapie._typing import ArrayLike, NDArray
 from mapie.conformity_scores import (ConformityScore,
-                                     FittedResidualNormalisingScore)
+                                     ConformalResidualFittingScore)
 from mapie.estimator.estimator import EnsembleRegressor
 from mapie.utils import (check_alpha, check_alpha_and_n_samples,
                          check_conformity_score, check_cv,
@@ -420,7 +420,7 @@ def _check_fit_parameters(
         cs_estimator = check_conformity_score(
             self.conformity_score
         )
-        if isinstance(cs_estimator, FittedResidualNormalisingScore) and \
+        if isinstance(cs_estimator, ConformalResidualFittingScore) and \
            self.cv not in ["split", "prefit"]:
             raise ValueError(
                 "The FittedResisualNormalizingScore can be used only with "

diff --git a/mapie/tests/test_conformity_scores.py b/mapie/tests/test_conformity_scores.py
@@ -10,7 +10,7 @@
 from mapie.conformity_scores import (AbsoluteConformityScore,
                                      ConformityScore,
                                      GammaConformityScore,
-                                     FittedResidualNormalisingScore)
+                                     ConformalResidualFittingScore)
 from mapie.regression import MapieRegressor
 
 X_toy = np.array([0, 1, 2, 3, 4, 5]).reshape(-1, 1)
@@ -231,7 +231,7 @@ def test_crf_prefit_conformity_score_get_conformity_scores(
     when prefit is True.
     """
     residual_estimator = LinearRegression().fit(X_toy, y_toy)
-    crf_conf_score = FittedResidualNormalisingScore(
+    crf_conf_score = ConformalResidualFittingScore(
         residual_estimator=residual_estimator,
         prefit=True,
         random_state=random_state
@@ -249,7 +249,7 @@ def test_crf_conformity_score_get_conformity_scores(y_pred: NDArray) -> None:
     Test conformity score computation for ConformalResidualFittingScore
     when prefit is False.
     """
-    crf_conf_score = FittedResidualNormalisingScore(random_state=random_state)
+    crf_conf_score = ConformalResidualFittingScore(random_state=random_state)
     conf_scores = crf_conf_score.get_conformity_scores(
         X_toy, y_toy, y_pred
     )
@@ -261,7 +261,7 @@ def test_crf_conformity_score_get_conformity_scores(y_pred: NDArray) -> None:
 
 def test_crf_score_prefit_with_notfitted_estim() -> None:
     """Test that a not fitted estimator and prefit=True raises an error."""
-    crf_conf_score = FittedResidualNormalisingScore(
+    crf_conf_score = ConformalResidualFittingScore(
             residual_estimator=LinearRegression(), prefit=True
     )
     with pytest.raises(ValueError):
@@ -272,7 +272,7 @@ def test_crf_score_prefit_with_notfitted_estim() -> None:
 
 def test_crf_score_prefit_with_default_params() -> None:
     """Test that no error is raised with default parameters."""
-    crf_conf_score = FittedResidualNormalisingScore()
+    crf_conf_score = ConformalResidualFittingScore()
     conf_scores = crf_conf_score.get_conformity_scores(
         X_toy, y_toy, y_pred_list
     )
@@ -286,7 +286,7 @@ class DumbEstimator:
         def __init__(self):
             pass
 
-    crf_conf_score = FittedResidualNormalisingScore(
+    crf_conf_score = ConformalResidualFittingScore(
         residual_estimator=DumbEstimator()
     )
     with pytest.raises(ValueError):
@@ -298,7 +298,7 @@ def __init__(self):
 def test_cross_crf() -> None:
     """Test that crf score called with cross method raises an error."""
     with pytest.raises(ValueError):
-        MapieRegressor(conformity_score=FittedResidualNormalisingScore()).fit(
+        MapieRegressor(conformity_score=ConformalResidualFittingScore()).fit(
             X_toy, y_toy
         )
 
@@ -312,7 +312,7 @@ def test_crf_score_pipe() -> None:
             ("linear", LinearRegression())
         ])
     mapie_reg = MapieRegressor(
-        conformity_score=FittedResidualNormalisingScore(
+        conformity_score=ConformalResidualFittingScore(
             residual_estimator=pipe, split_size=0.2
         ),
         cv="split",
@@ -333,7 +333,7 @@ def test_crf_score_pipe_prefit() -> None:
         ])
     pipe.fit(X_toy, y_toy)
     mapie_reg = MapieRegressor(
-        conformity_score=FittedResidualNormalisingScore(
+        conformity_score=ConformalResidualFittingScore(
             residual_estimator=pipe, split_size=0.2, prefit=True
         ),
         cv="split",

diff --git a/mapie/tests/test_regression.py b/mapie/tests/test_regression.py
@@ -23,7 +23,7 @@
 from mapie.conformity_scores import (AbsoluteConformityScore,
                                      ConformityScore,
                                      GammaConformityScore,
-                                     FittedResidualNormalisingScore)
+                                     ConformalResidualFittingScore)
 from mapie.metrics import regression_coverage_score
 from mapie.regression import MapieRegressor
 from mapie.estimator.estimator import EnsembleRegressor
@@ -593,7 +593,7 @@ def test_conformity_score(
 
 
 @pytest.mark.parametrize(
-    "conformity_score", [FittedResidualNormalisingScore()]
+    "conformity_score", [ConformalResidualFittingScore()]
 )
 def test_conformity_score_with_split_strategies(
    conformity_score: ConformityScore