public code v1

pygrex/explain/individual/model_based_emf.py

@@ -0,0 +1,28 @@
+from .explainer import Explainer
+
+
+class EMFExplainer(Explainer):
+    def __init__(self, model, recommendations, data):
+        super(EMFExplainer, self).__init__(model, recommendations, data)
+
+    def explain_recommendation_to_user(self, user_id: int, item_id: int):
+        """
+        Measuring the contribution of each item to the recommendation.
+        :param user_id:
+        :param item_id: recommendation
+        :return: returns a dataframe with the contribution to the recommendation of each previously interacted with item.
+        """
+
+        ratings_on_item = self.dataset[self.dataset.itemId == item_id]
+        similar_users = self.model.sim_users[user_id]
+        similar_users_ratings_on_item = ratings_on_item[
+            ratings_on_item.userId.isin(similar_users)
+        ]
+
+        explanation_df = similar_users_ratings_on_item.groupby(by="rating").count()
+        explanation = {}
+
+        for index, row in explanation_df.iterrows():
+            explanation[index] = row[0]
+
+        return explanation