@@ -31,23 +31,23 @@ The project is organized into the following key components:
...
@@ -31,23 +31,23 @@ The project is organized into the following key components:
###Data Loaders
###Data Loaders
3.**loaders.py**
3.**loaders.py**
-Loads rating and item data from specified CSV files in the Constant class of the constants module.
Loads rating and item data from specified CSV files in the Constant class of the constants module.
-The `load_ratings` function loads rating data.
The `load_ratings` function loads rating data.
-The `load_items` function loads item data.
The `load_items` function loads item data.
-The `export_evaluation_report` function merges rating and item data, then exports the evaluation report to a CSV file.
The `export_evaluation_report` function merges rating and item data, then exports the evaluation report to a CSV file.
-The data is loaded into pandas DataFrames, with an option available to load rating data in the format expected by the Surprise library if needed.
The data is loaded into pandas DataFrames, with an option available to load rating data in the format expected by the Surprise library if needed.
###Recommender Models
###Recommender Models
4.**models.py**
4.**models.py**
- Defines several basic recommendation algorithms for the Surprise library.
Defines several basic recommendation algorithms for the Surprise library.
The get_top_n function takes a list of predictions and returns the top recommendations for each user.
- The get_top_n function takes a list of predictions and returns the top recommendations for each user.
-
Recommendation algorithms are defined as classes inheriting from Surprise's AlgoBase class, each implementing an estimate method to predict user ratings for items.=======
Recommendation algorithms are defined as classes inheriting from Surprise's AlgoBase class, each implementing an estimate method to predict user ratings for items.=======
Ces codes se trouveront dans le même dossier que chacun des jupyter notebook (.ipynb).
Ces codes se trouveront dans le même dossier que chacun des jupyter notebook (.ipynb).