MAINT Parameters validation for sklearn.covariance.log_likelihood (scikit-learn#26539)

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

Author: Stamic-kk

sklearn/covariance/_empirical_covariance.py

@@ -23,6 +23,13 @@
 from ..utils.extmath import fast_logdet
 
 
+@validate_params(
+    {
+        "emp_cov": [np.ndarray],
+        "precision": [np.ndarray],
+    },
+    prefer_skip_nested_validation=True,
+)
 def log_likelihood(emp_cov, precision):
     """Compute the sample mean of the log_likelihood under a covariance model.
 

sklearn/tests/test_public_functions.py

@@ -139,6 +139,7 @@ def _check_function_param_validation(
     "sklearn.cluster.ward_tree",
     "sklearn.covariance.empirical_covariance",
     "sklearn.covariance.ledoit_wolf_shrinkage",
+    "sklearn.covariance.log_likelihood",
     "sklearn.covariance.shrunk_covariance",
     "sklearn.datasets.clear_data_home",
     "sklearn.datasets.dump_svmlight_file",