[python-package] ignore scikit-learn 'check_sample_weight_equivalence'...

[python-package] ignore scikit-learn 'check_sample_weight_equivalence' estimator check (fixes #6678) (#6679)

* [python-package] ignore scikit-learn 'check_sample_weight_equivalence' estimator check (fixes #6678)

* pin pyparsing in Python 3.8 environment

.ci/conda-envs/ci-core-py38.txt

@@ -41,6 +41,7 @@ bokeh=3.1.*
 fsspec=2024.5.*
 msgpack-python=1.0.*
 pluggy=1.5.*
+pyparsing=3.1.4
 pytz=2024.1
 setuptools=69.5.*
 snappy=1.2.*

python-package/lightgbm/sklearn.py

@@ -678,6 +678,12 @@ class LGBMModel(_LGBMModelBase):
                 "check_no_attributes_set_in_init": "scikit-learn incorrectly asserts that private attributes "
                 "cannot be set in __init__: "
                 "(see https://github.com/microsoft/LightGBM/issues/2628)",
+                "check_sample_weight_equivalence": (
+                    "In LightGBM, setting a sample's weight to 0 can produce a different result than omitting the sample. "
+                    "Such samples intentionally still affect count-based measures like 'min_data_in_leaf' "
+                    "(https://github.com/microsoft/LightGBM/issues/5626#issuecomment-1712706678) and the estimated distribution "
+                    "of features for Dataset construction (see https://github.com/microsoft/LightGBM/issues/5553)."
+                ),
             },
         }