[python-package] Allow to pass early stopping min delta in params

python-package/lightgbm/engine.py

@@ -241,6 +241,7 @@ def train(
             callback.early_stopping(
                 stopping_rounds=params["early_stopping_round"],  # type: ignore[arg-type]
                 first_metric_only=first_metric_only,
+                min_delta=params.get("early_stopping_min_delta", 0.0),
                 verbose=_choose_param_value(
                     main_param_name="verbosity",
                     params=params,
@@ -765,6 +766,7 @@ def cv(
             callback.early_stopping(
                 stopping_rounds=params["early_stopping_round"],  # type: ignore[arg-type]
                 first_metric_only=first_metric_only,
+                min_delta=params.get("early_stopping_min_delta", 0.0),
                 verbose=_choose_param_value(
                     main_param_name="verbosity",
                     params=params,

tests/python_package_test/test_engine.py

@@ -938,6 +938,29 @@ def test_early_stopping_via_global_params(first_metric_only):
     assert "error" in gbm.best_score[valid_set_name]
 
 
+@pytest.mark.parametrize("early_stopping_min_delta", [1e3, 0.0])
+def test_early_stopping_min_delta_via_global_params(early_stopping_min_delta):
+    X, y = load_breast_cancer(return_X_y=True)
+    num_trees = 5
+    params = {
+        "num_trees": num_trees,
+        "objective": "binary",
+        "metric": "None",
+        "verbose": -1,
+        "early_stopping_round": 2,
+        "early_stopping_min_delta": early_stopping_min_delta,
+    }
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=42)
+    lgb_train = lgb.Dataset(X_train, y_train)
+    lgb_eval = lgb.Dataset(X_test, y_test, reference=lgb_train)
+    valid_set_name = "valid_set"
+    gbm = lgb.train(params, lgb_train, feval=decreasing_metric, valid_sets=lgb_eval, valid_names=valid_set_name)
+    if early_stopping_min_delta == 0:
+        assert gbm.best_iteration == num_trees
+    else:
+        assert gbm.best_iteration == 1
+
+
 @pytest.mark.parametrize("first_only", [True, False])
 @pytest.mark.parametrize("single_metric", [True, False])
 @pytest.mark.parametrize("greater_is_better", [True, False])