Merge branch 'Project' of https://forge.uclouvain.be/recommender_system/recomsys into Project

recommender.py

@@ -7,6 +7,7 @@ from collections import defaultdict
 # Third-party imports
 import numpy as np
 import pandas as pd
+import matplotlib.pyplot as plt
 
 from scipy.stats import pearsonr
 from sklearn.ensemble import AdaBoostRegressor, GradientBoostingRegressor, RandomForestRegressor
@@ -23,7 +24,6 @@ from sklearn.svm import SVR
 from sklearn.tree import DecisionTreeRegressor
 from surprise import AlgoBase, KNNWithMeans, accuracy, PredictionImpossible
 from xgboost import XGBRegressor
-from lightgbm import LGBMRegressor
 
 # Local imports
 from constants import Constant as C
@@ -345,6 +345,19 @@ class RecommenderSystem_KNN :
         predictions = self.model.test(self.testset)
         self.rmse = accuracy.rmse(predictions)
     
+    def evaluate_rmse(self, testset):
+        """
+        Evaluate the RMSE of the model on a test set.
+
+        Args:
+            testset (list): List of testset entries containing (user, item, rating).
+
+        Returns:
+            float: RMSE of the model.
+        """
+        predictions = self.model.test(self.testset)
+        return accuracy.rmse(predictions, verbose=True)
+
     def evaluate_mae(self):
         """
         Evaluate the MAE of the model on the test set.