Surprise
A Python scikit for building and analyzing recommender systems
Language: python
Author: Camilla Döring (@camilla)
12 stars · 331 views
Files
- CHANGELOG.md (markdown)
- building_custom_algorithms ()
- prediction_algorithms ()
- README.md (markdown)
- doc ()
- source ()
- examples ()
- conf.py (python)
- grid_search_usage.py (python)
- most_basic_algorithm2.py (python)
- run_all_examples.py (python)
- load_custom_dataset_predefined_folds.py (python)
- serialize_algorithm.py (python)
- load_from_dataframe.py (python)
- surprise ()
- model_selection ()
- dataset.py (python)
- predictions.py (python)
- setup.py (python)
- __main__.py (python)
- __init__.py (python)
- load_custom_dataset.py (python)
- split_data_for_unbiased_estimation.py (python)
- top_n_recommendations.py (python)
- accuracy.py (python)
- __init__.py (python)
- baseline_only.py (python)
- algo_base.py (python)
- LICENSE.md (markdown)
- lint.sh (bash)
- evaluate_on_trainset.py (python)
- make.bat (plaintext)
- k_nearest_neighbors.py (python)
- precision_recall_at_k.py (python)
- similarity_conf.py (python)
- split.py (python)
- search.py (python)
- benchmark.py (python)
- CONTRIBUTING.md (markdown)
- generate_grid_search_cv_results_example.py (python)
- mean_rating_user_item.py (python)
- pyproject.toml (toml)
- use_cross_validation_iterators.py (python)
- __init__.py (python)
- basic_usage.py (python)
- most_basic_algorithm.py (python)
- validation.py (python)
- trainset.py (python)
- baselines_conf.py (python)
- TODO.md (markdown)
- predict_ratings.py (python)
- builtin_datasets.py (python)
- dump.py (python)
- reader.py (python)
- random_pred.py (python)
- knns.py (python)
- ATTRIBUTION.md (markdown)
- with_baselines_or_sim.py (python)