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Valider c7598c01 rédigé par Prince Addae's avatar Prince Addae
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...@@ -66,11 +66,11 @@ The project is organized into the following key components: ...@@ -66,11 +66,11 @@ The project is organized into the following key components:
- Evaluates different recommendation models using various cross-validation techniques. - Evaluates different recommendation models using various cross-validation techniques.
- Imports key packages and modules (model_selection and accuracy from Surprise). - Imports key packages and modules (`model_selection` and `accuracy` from Surprise).
- Adapts the load_ratings function to load data in a format compatible with Surprise. - Adapts the `load_ratings` function to load data in a format compatible with Surprise.
- Implements three methods of cross-validation: generate_split_predictions, generate_loo_top_n, and generate_full_top_n. - Implements three methods of cross-validation: `generate_split_predictions,` `generate_loo_top_n`, and `generate_full_top_n`.
- Introduces three new metrics: RMSE, hit rate, and novelty. - Introduces three new metrics: RMSE, hit rate, and novelty.
...@@ -81,13 +81,13 @@ The project is organized into the following key components: ...@@ -81,13 +81,13 @@ The project is organized into the following key components:
- Analyzes a smaller version of the dataset for debugging purposes. - Analyzes a smaller version of the dataset for debugging purposes.
- Similar analyses to analytics_ui.ipynb, but on a smaller scale to speed up computation time. - Similar analyses to `analytics_ui.ipynb`, but on a smaller scale to speed up computation time.
8. ***analytics_test.ipynb*** 8. ***analytics_test.ipynb***
- Analyzes a test dataset to understand algorithm behaviors during development. - Analyzes a test dataset to understand algorithm behaviors during development.
- Similar analyses to analytics_ui.ipynb, but on a smaller test dataset to better understand how algorithms work. - Similar analyses to `analytics_ui.ipynb`, but on a smaller test dataset to better understand how algorithms work.
### Datasets ### Datasets
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