0.8.0 🌈

Changes

🚀 Features

• remove pyyaml & explicit scikit-learn (#729) @Zethson
• Remove fancyimpute (#728) @Zethson
• Unify feature type detection (#724) @Lilly-May
• catplot (#721) @eroell
• Simplify ehrapy (#719) @Zethson
• Use all (#715) @Zethson
• Add bias detection to preprocessing (#690) @Lilly-May
• Use lamin logger (#707) @Zethson
• Add faiss backend for KNN imputation (#704) @Zethson
• Build RTD docs with uv (#700) @Zethson
• Refactor feature importance ranking (#698) @Zethson
• Simplify CI (#694) @Zethson
• Refactor outliers and IQR (#692) @Zethson
• Calculation of feature importances in a supervised setting (#677) @Lilly-May
• Speed up winsorize (#681) @Zethson
• Remove notebook prefix in tutorial URLs (#679) @Zethson
• Add cohort tracking notebook (#678) @Zethson
• Switch to uv (#674) @Zethson
• Style: typing of _scale_func_group (#727) @eroell
• Improved support of encoded features in detect_bias (#725) @Lilly-May
• Enable Synchronous dataloader write (#722) @wxicu
• Feature scaling on training set when computing feature importances (#716) @Lilly-May
• add batch-wise normalization argument (#711) @eroell
• add functools.wraps to type check (#705) @eroell
• add bias notebook to list of notebooks (#696) @eroell
• basic sampling (#686) @eroell
• add options for subitles in legend of cohorttrackers barplot (#688) @eroell
• doc fix imputation: 70 instead of 30 (#683) @eroell

🐛 Bug Fixes

• Encoded dtype to float32 instead of np.number (#714) @Zethson
• Fix feature importance warnings (#708) @Zethson
• Remove notebook prefix in tutorial URLs (#679) @Zethson
• fix name of log_rogistic_aft to log_logistic_aft (#676) @eroell

🧰 Maintenance

• Remove notebook prefix in tutorial URLs (#679) @Zethson
• Add cohort tracking notebook (#678) @Zethson
• knni amendments (#706) @eroell