Rename `AggregateMeanFScore` to `AggregateMeanFScoreEvaluator`

ahisto_named_entity_search/recognition/__init__.py

 from .evaluator import (
-    AggregateMeanFScore,
+    AggregateMeanFScoreEvaluator,
 )
 
 from .model import (
@@ -14,7 +14,7 @@ from .schedule import (
 
 
 __all__ = [
-    'AggregateMeanFScore',
+    'AggregateMeanFScoreEvaluator',
     'get_schedule',
     'NerModel',
     'ScheduleName',

ahisto_named_entity_search/recognition/evaluator.py

@@ -18,7 +18,7 @@ GroupMap = Dict[GroupName, Group]
 FScore = float
 
 
-class AggregateMeanFScore(TokenClassificationEvaluator):
+class AggregateMeanFScoreEvaluator(TokenClassificationEvaluator):
     GROUPS: GroupMap = {
         'PER': {'B-PER', 'I-PER', 'B-ORG', 'I-ORG'},
         'LOC': {'B-LOC', 'I-LOC', 'B-ORG', 'I-ORG'},

ahisto_named_entity_search/recognition/model.py

@@ -16,13 +16,13 @@ from ..config import CONFIG as _CONFIG
 from ..document import Document, Sentence
 from ..search import TaggedSentence, NerTags
 from .schedule import ScheduleName, get_schedule
-from .evaluator import AggregateMeanFScore, FScore, CategoryMap, CategoryName
+from .evaluator import AggregateMeanFScoreEvaluator, FScore, CategoryMap, CategoryName
 
 
 LOGGER = getLogger(__name__)
 
 
-EvaluationResult = Dict[AggregateMeanFScore, FScore]
+EvaluationResult = Dict[AggregateMeanFScoreEvaluator, FScore]
 
 
 class NerModel:
@@ -172,12 +172,12 @@ def load_ner_dataset(tagged_sentence_basename: str) -> Tuple[List[Sentence], Lis
     return ner_texts, all_ner_tags
 
 
-def get_evaluators(labels: Iterable[str]) -> Iterable[AggregateMeanFScore]:
+def get_evaluators(labels: Iterable[str]) -> Iterable[AggregateMeanFScoreEvaluator]:
     category_map: CategoryMap = {
         category: category_index
         for category_index, category
         in enumerate(sorted(labels))
     }
-    for group_name in AggregateMeanFScore.get_all_group_names():
-        yield AggregateMeanFScore(category_map, group_name, decides_convergence=False)
-    yield AggregateMeanFScore(category_map, None, decides_convergence=True)
+    for group_name in AggregateMeanFScoreEvaluator.get_all_group_names():
+        yield AggregateMeanFScoreEvaluator(category_map, group_name, decides_convergence=False)
+    yield AggregateMeanFScoreEvaluator(category_map, None, decides_convergence=True)