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[pyspark] Add param validation for "objective" and "eval_metric" param, and remove invalid booster params (#8173)

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Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
This commit is contained in:
WeichenXu
2022-08-24 15:29:43 +08:00
committed by GitHub
parent 9b32e6e2dc
commit d03794ce7a
3 changed files with 26 additions and 4 deletions
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2
tests/python/test_spark/test_spark_local.py
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@@ -433,6 +433,7 @@ class XgboostLocalTest(SparkTestCase):
self.assertEqual(py_reg.n_estimators.parent, py_reg.uid)
self.assertFalse(hasattr(py_reg, "gpu_id"))
self.assertEqual(py_reg.getOrDefault(py_reg.n_estimators), 100)
self.assertEqual(py_reg.getOrDefault(py_reg.objective), "reg:squarederror")
py_reg2 = SparkXGBRegressor(n_estimators=200)
self.assertEqual(py_reg2.getOrDefault(py_reg2.n_estimators), 200)
py_reg3 = py_reg2.copy({py_reg2.max_depth: 10})
@@ -445,6 +446,7 @@ class XgboostLocalTest(SparkTestCase):
self.assertEqual(py_cls.n_estimators.parent, py_cls.uid)
self.assertFalse(hasattr(py_cls, "gpu_id"))
self.assertEqual(py_cls.getOrDefault(py_cls.n_estimators), 100)
self.assertEqual(py_cls.getOrDefault(py_cls.objective), None)
py_cls2 = SparkXGBClassifier(n_estimators=200)
self.assertEqual(py_cls2.getOrDefault(py_cls2.n_estimators), 200)
py_cls3 = py_cls2.copy({py_cls2.max_depth: 10})