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Copy file name to clipboardExpand all lines: CHANGELOG.md
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## Unreleased
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### Added
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-`VisualApp` and `ItemToItemVisualApp` widgets for visual comparison of recommendations ([#80](https://github.com/MobileTeleSystems/RecTools/pull/80), [#82](https://github.com/MobileTeleSystems/RecTools/pull/82), [#85](https://github.com/MobileTeleSystems/RecTools/pull/85)) (Need examples and readme update)
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-`VisualApp` and `ItemToItemVisualApp` widgets for visual comparison of recommendations ([#80](https://github.com/MobileTeleSystems/RecTools/pull/80), [#82](https://github.com/MobileTeleSystems/RecTools/pull/82), [#85](https://github.com/MobileTeleSystems/RecTools/pull/85), [#115](https://github.com/MobileTeleSystems/RecTools/pull/115))
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- Methods for conversion `Interactions` to raw form and for getting raw interactions from `Dataset` ([#69](https://github.com/MobileTeleSystems/RecTools/pull/69))
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-`AvgRecPopularity (Average Recommendation Popularity)` to `metrics` ([#81](https://github.com/MobileTeleSystems/RecTools/pull/81))
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- Added `normalized` parameter to `AvgRecPopularity` metric ([#89](https://github.com/MobileTeleSystems/RecTools/pull/89))
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### Fixed
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- Bug in `Interactions.from_raw` method ([#58](https://github.com/MobileTeleSystems/RecTools/pull/58))
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- Mistakes in formulas for Serendipity and MIUF in docstrings ([#115](https://github.com/MobileTeleSystems/RecTools/pull/115))
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- Examples reproducibility on Google Colab ([#115](https://github.com/MobileTeleSystems/RecTools/pull/115))
Copy file name to clipboardExpand all lines: README.md
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-`lightfm`: adds wrapper for LightFM model,
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-`torch`: adds models based on neural nets,
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-`visuals`: adds visualization tools,
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-`nmslib`: adds fast ANN recommenders.
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Install extension:
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|[implicit](https://github.com/benfred/implicit) ALS Wrapper | Matrix Factorization |`rectools.models.ImplicitALSWrapperModel` - Alternating Least Squares Matrix Factorizattion algorithm for implicit feedback | Support for user/item features! [Check our boost to metrics](examples/5_benchmark_iALS_with_features.ipynb)|
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|[implicit](https://github.com/benfred/implicit) ItemKNN Wrapper | Collaborative Filtering |`rectools.models.ImplicitItemKNNWrapperModel` - Algorithm that calculates item-item similarity matrix using distances between item vectors in user-item interactions matrix | - |
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|[LightFM](https://github.com/lyst/lightfm) Wrapper | Matrix Factorization |`rectools.models.LightFMWrapperModel` - Hybrid matrix factorization algorithm which utilises user and item features and supports a variety of losses | 10-25 times faster inference! [Check our boost to inference](examples/6_benchmark_lightfm_inference.ipynb)|
| PureSVD | Matrix Factorization |`rectools.models.PureSVDModel` - Truncated Singular Value Decomposition of user-item interactions matrix | - |
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| DSSM | Neural Network |`rectools.models.DSSMModel` - Two-tower Neural model that learns user and item embeddings utilising their explicit features and learning on triplet loss | - |
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| Popular | Heuristic |`rectools.models.PopularModel` - Classic baseline which computes popularity of items | Hyperparams (time window, pop computation) |
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