Use mean instead of sum for similarity to improve understandability

2 files changed, 8 insertions, 3 deletions

diff --git a/mlscraper/matches.py b/mlscraper/matches.py
index 3b039d5..d34c430 100644
--- a/mlscraper/matches.py
+++ b/mlscraper/matches.py
@@ -6,6 +6,7 @@ import typing
 from functools import cached_property
 from itertools import combinations
 from itertools import product
+from statistics import mean
 
 from mlscraper.html import get_relative_depth
 from mlscraper.html import get_root_node
@@ -135,7 +136,7 @@ class DictMatch(Match):
         keys = set(self.match_by_key.keys()).intersection(
             set(match.match_by_key.keys())
         )
-        return sum(
+        return mean(
             self.match_by_key[key].get_similarity_to(match.match_by_key[key])
             for key in keys
         )
@@ -163,7 +164,7 @@ class ListMatch(Match):
 
     def get_similarity_to(self, match: "Match"):
         assert isinstance(match, self.__class__)
-        return sum(
+        return mean(
             lm1.get_similarity_to(lm2)
             for lm1, lm2 in product(self.matches, match.matches)
         )
diff --git a/mlscraper/training.py b/mlscraper/training.py
index 3e3b259..d9b1b8a 100644
--- a/mlscraper/training.py
+++ b/mlscraper/training.py
@@ -1,6 +1,7 @@
 import logging
 from itertools import combinations
 from itertools import product
+from statistics import mean
 
 from mlscraper.matches import DictMatch
 from mlscraper.matches import ListMatch
@@ -25,8 +26,11 @@ class NoScraperFoundException(TrainingException):
 
 
 def get_match_combination_priority(matches):
+    if len(matches) == 1:
+        return 1
+
     # check for similarity between matches
-    return sum(m1.get_similarity_to(m2) for m1, m2 in combinations(matches, 2))
+    return mean(m1.get_similarity_to(m2) for m1, m2 in combinations(matches, 2))
 
 
 def train_scraper(training_set: TrainingSet, complexity=100):