work on test.

Author: trivialfis

tests/python/test_eval_metrics.py

@@ -317,6 +317,26 @@ def run_pr_auc_ltr(self, tree_method):
     def test_pr_auc_ltr(self):
         self.run_pr_auc_ltr("hist")
 
+    def test_precision_score(self):
+        from sklearn.metrics import precision_score
+        from sklearn.datasets import make_classification
+
+        x, y = make_classification(n_samples=128, n_features=4, n_classes=2)
+        qid = np.zeros(shape=y.shape)  # same group
+
+        ltr = xgb.XGBRanker()
+        ltr.fit(x, y, qid=qid)
+        p = ltr.predict(x)
+        sorted_idx = np.argsort(p)
+
+        score_0 = precision_score(y, y[sorted_idx])
+        print(score_0)
+
+        Xy = xgb.DMatrix(x, y)
+        ltr.set_params(eval_metric="pre")
+        e = ltr.get_booster().eval_set(evals=[(Xy, "Xy")])
+        print(e)
+
     @pytest.mark.skipif(**tm.no_sklearn())
     def test_quantile_error(self) -> None:
         check_quantile_error("hist")