Add

1) read entities from Db
2) read tags - entities into entity_tags DICT
3) Chaned Clasifier into naive Bayes
4) Into classify- Method add 'entity_id' int field to increase tag likelihood.

news_classify_tag.py

@@ -204,12 +204,12 @@ class Classifier:
         rez = self.classifier.predict_proba(matrix_test_data)
         # exit(0)
         self.likelihood_list = rez[0]
-        print("Entitys tags:", end="")
+        # print("Entitys tags:", end="")
         if entity_id != 0:
             if entity_id in self.entity_tags.keys():
                 rez = str(self.entity_tags[entity_id])
                 tags_list_from_entity = list(int(item) for item in rez.split(" "))
-                print(tags_list_from_entity)
+                # print(tags_list_from_entity)
 
                 for item_num, tag_id, in enumerate(self.links_tags):
                     if tag_id in tags_list_from_entity and self.likelihood_list[item_num] < 0.1: