Change model from 'frequency matrix model' into 'Direct model'

Changed into accordance list binary string data -> string data

news_classify_tag.py

@@ -119,7 +119,6 @@ class Classifier:
 
     @property
     def teg_accordance(self, persantage=20):
-
         """
         Class method for computing % af tag accordance 
         :return: tuple of % af tag accordance
@@ -129,7 +128,8 @@ class Classifier:
             temp_matrix = self.tag_frequency_matrix[row]
             rez_summ = temp_matrix[self.matrix_test_data.toarray ()[0] > 0].sum ()
             if rez_summ > (persantage / 100):
-                vector_accordance.append ((int(self.tags[row][0]), int (rez_summ * 1000) / 10, self.tags[row][1].decode('ascii', 'ignore')))
+                vector_accordance.append (
+                    (int (self.tags[row][0]), int (rez_summ * 1000) / 10, self.tags[row][1].decode ('ascii', 'ignore')))
             vector_accordance.sort (key=lambda tup: tup[1], reverse=True)
 
         return vector_accordance
@@ -249,7 +249,7 @@ if __name__ == "__main__":
         for (tag,) in tags:
             tag = int (tag)
             # print(tag)
-            print (str (tag) + " " + tags_classif.tags[tag-1][1].decode ('ascii', 'ignore'))
+            print (str (tag) + " " + tags_classif.tags[tag - 1][1].decode ('ascii', 'ignore'))
 
     exit (0)
     tags_classif.db.query ("SELECT title, description FROM wp_esi_news ORDER BY RAND() LIMIT 25")
@@ -270,4 +270,4 @@ if __name__ == "__main__":
         # if i > 10: break
 
         # Graph presentation results
-        # tags_classif.graph_results()
+        tags_classif.graph_results ()