Use _validate_params in Birch

kianelbo · kianelbo · commit 1438dedf7f5a · 2022-06-11T23:25:48.000+04:30
diff --git a/sklearn/cluster/_birch.py b/sklearn/cluster/_birch.py
@@ -4,8 +4,8 @@
 # License: BSD 3 clause
 
 import warnings
-import numbers
 import numpy as np
+from numbers import Integral, Real
 from scipy import sparse
 from math import sqrt
 
@@ -19,6 +19,7 @@
 )
 from ..utils.extmath import row_norms
 from ..utils import check_scalar, deprecated
+from ..utils._param_validation import Interval
 from ..utils.validation import check_is_fitted
 from ..exceptions import ConvergenceWarning
 from . import AgglomerativeClustering
@@ -478,6 +479,14 @@ class Birch(
     array([0, 0, 0, 1, 1, 1])
     """
 
+    _parameter_constraints = {
+        "threshold": [Interval(Real, 0.0, 1.0, closed="neither")],
+        "branching_factor": [Interval(Integral, 1, None, closed="left")],
+        "n_clusters": [None, ClusterMixin, Interval(Integral, 1, None, closed="left")],
+        "compute_labels": [bool],
+        "copy": [bool],
+    }
+
     def __init__(
         self,
         *,
@@ -529,28 +538,7 @@ def fit(self, X, y=None):
             Fitted estimator.
         """
 
-        # Validating the scalar parameters.
-        check_scalar(
-            self.threshold,
-            "threshold",
-            target_type=numbers.Real,
-            min_val=0.0,
-            include_boundaries="neither",
-        )
-        check_scalar(
-            self.branching_factor,
-            "branching_factor",
-            target_type=numbers.Integral,
-            min_val=1,
-            include_boundaries="neither",
-        )
-        if isinstance(self.n_clusters, numbers.Number):
-            check_scalar(
-                self.n_clusters,
-                "n_clusters",
-                target_type=numbers.Integral,
-                min_val=1,
-            )
+        self._validate_params()
 
         # TODO: Remove deprecated flags in 1.2
         self._deprecated_fit, self._deprecated_partial_fit = True, False
@@ -744,7 +732,7 @@ def _global_clustering(self, X=None):
 
         # Preprocessing for the global clustering.
         not_enough_centroids = False
-        if isinstance(clusterer, numbers.Integral):
+        if isinstance(clusterer, Integral):
             clusterer = AgglomerativeClustering(n_clusters=self.n_clusters)
             # There is no need to perform the global clustering step.
             if len(centroids) < self.n_clusters:
diff --git a/sklearn/cluster/tests/test_birch.py b/sklearn/cluster/tests/test_birch.py
@@ -186,40 +186,6 @@ def test_birch_fit_attributes_deprecated(attribute):
         getattr(brc, attribute)
 
 
-@pytest.mark.parametrize(
-    "params, err_type, err_msg",
-    [
-        ({"threshold": -1.0}, ValueError, "threshold == -1.0, must be > 0.0."),
-        ({"threshold": 0.0}, ValueError, "threshold == 0.0, must be > 0.0."),
-        ({"branching_factor": 0}, ValueError, "branching_factor == 0, must be > 1."),
-        ({"branching_factor": 1}, ValueError, "branching_factor == 1, must be > 1."),
-        (
-            {"branching_factor": 1.5},
-            TypeError,
-            "branching_factor must be an instance of int, not float.",
-        ),
-        ({"branching_factor": -2}, ValueError, "branching_factor == -2, must be > 1."),
-        ({"n_clusters": 0}, ValueError, "n_clusters == 0, must be >= 1."),
-        (
-            {"n_clusters": 2.5},
-            TypeError,
-            "n_clusters must be an instance of int, not float.",
-        ),
-        (
-            {"n_clusters": "whatever"},
-            TypeError,
-            "n_clusters should be an instance of ClusterMixin or an int",
-        ),
-        ({"n_clusters": -3}, ValueError, "n_clusters == -3, must be >= 1."),
-    ],
-)
-def test_birch_params_validation(params, err_type, err_msg):
-    """Check the parameters validation in `Birch`."""
-    X, _ = make_blobs(n_samples=80, centers=4)
-    with pytest.raises(err_type, match=err_msg):
-        Birch(**params).fit(X)
-
-
 def test_feature_names_out():
     """Check `get_feature_names_out` for `Birch`."""
     X, _ = make_blobs(n_samples=80, n_features=4, random_state=0)
diff --git a/sklearn/tests/test_common.py b/sklearn/tests/test_common.py
@@ -459,7 +459,6 @@ def test_estimators_do_not_raise_errors_in_init_or_set_params(Estimator):
     "BernoulliNB",
     "BernoulliRBM",
     "Binarizer",
-    "Birch",
     "CCA",
     "CalibratedClassifierCV",
     "CategoricalNB",
