fix

README.md

@@ -14,7 +14,7 @@ pinned: false
 # Metric Card for mrr
 
 ## Metric Description
-This is the mean average precision (map) metric for retrieval systems.
+This is the mean reciprocal rank (mrr) metric for retrieval systems.
 It is the average of the precision scores computer after each relevant document is got. You can refer to [here](https://amenra.github.io/ranx/metrics/#mean-reciprocal-rank)
 
 ## How to Use

mrr.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""Mean average precision metric"""
+"""Mean reciprocal rank metric"""
 
 import evaluate
 import datasets
@@ -62,7 +62,7 @@ Examples:
 """
 
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
-class map(evaluate.Metric):
+class mrr(evaluate.Metric):
     def _info(self):
         return evaluate.MetricInfo(
             # This is the description that will appear on the modules page.
@@ -73,8 +73,7 @@ class map(evaluate.Metric):
             # This defines the format of each prediction and reference
             features=datasets.Features({
                 'predictions':  datasets.Value("string"),
-                'references':  datasets.Value("string"),
-                'k': datasets.Value("int32")    
+                'references':  datasets.Value("string")
             }),
             # Homepage of the module for documentation
             reference_urls=["https://amenra.github.io/ranx/"]