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Recommendation Systems - IESEG School of Management

Project description

drawing
Recommendation Systems
Module
Class: 2022 & 2023

Overview

  • Model evaluation (eval.py):
    • Regression metrics
      • RMSE
      • MAE
    • Classification metrics
      • Precision
      • Recall
      • F1
    • Ranking metrics
      • NDCG
    • eval.evaluate computes all above mentioned metrics
    • Evaluate Top-N recommendations
      • HR
      • MAP
  • Content based Recommender System (model.py)
  • Helper functions (utils.py)
    • get_top_n: Compute Top-N recommendations from predictions
    • predict_user_topn: Compute Top-N recommendations for a user

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