0.6.0

✨ Highlights ✨

• Added support of recommendations for cold and warm users/items
• Added support for Python 3.11 and 3.12
• Stopped supporting Python 3.7 and old versions of some dependencies

All updates

Added

• Warm users/items support in Dataset (#77)
• Warm and cold users/items support in ModelBase and all possible models (#77, #120, #122)
• Warm and cold users/items support in cross_validate (#77)
• [Breaking] Default value for train dataset type and params for user and item dataset types in DSSMModel (#122)
• [Breaking] n_factors and deterministic params to DSSMModel (#122)
• Hit Rate metric (#124)
• Python 3.11 support (without nmslib) (#126)
• Python 3.12 support (without nmslib and lightfm) (#126)

Changed

• Changed the logic of choosing random sampler for RandomModel and increased the sampling speed (#120)
• [Breaking] Changed the logic of RandomModel: now the recommendations are different for repeated calls of recommend methods (#120)
• Torch datasets to support warm recommendations (#122)
• [Breaking] Replaced include_warm parameter in Dataset.get_user_item_matrix to pair include_warm_users and include_warm_items (#122)
• [Breaking] Renamed torch datasets and dataset_type to train_dataset_type param in DSSMModel (#122)
• [Breaking] Updated minimum versions of numpy, scipy, pandas, typeguard (#126)
• [Breaking] Set restriction scipy < 1.13 (#126)

Removed

• [Breaking] return_external_ids parameter in recommend and recommend_to_items model methods (#77)
• [Breaking] Python 3.7 support (#126)