Appease linter

tests/python_package_test/test_dask.py

@@ -1547,7 +1547,7 @@ def test_predict_stump(output, use_init_score, cluster, rng):
  with Client(cluster) as client:
  _, _, _, _, dX, dy, _, _ = _create_data(objective="binary-classification", n_samples=1_000, output=output)
 
- params = {"objective": "binary", "n_estimators": 5, "min_data_in_leaf": n_samples}
+ params = {"objective": "binary", "n_estimators": 5, "min_data_in_leaf": 1_000}
 
  if not use_init_score:
  init_scores = None
@@ -1557,7 +1557,7 @@ def test_predict_stump(output, use_init_score, cluster, rng):
  init_scores = dy.map_blocks(lambda x: rng.uniform(size=x.size))
 
  model = lgb.DaskLGBMClassifier(client=client, **params)
- model.fit(dX, dy, group=dg, init_score=init_scores)
+ model.fit(dX, dy, init_score=init_scores)
  preds_1 = model.predict(dX, raw_score=True, num_iteration=1).compute()
  preds_all = model.predict(dX, raw_score=True).compute()