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Releases: nubank/fklearn

2.1.0

27 Jul 13:37
87dd877
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  • Enhancement
    • Add optional parameter return_eval_logs_on_train to the validator function,
      enabling it to return the evaluation logs for all training folds instead of just
      the first one
  • Bug Fix
    • Fix import in pd_extractors.py for Python 3.10 compatibility
    • Set a minimal version of Python (3.6.2) for Fklearn
  • Documentation
    • Fixing some typos, broken links and general improvement on the documentation

2.0.0

30 Dec 01:17
aa558fb
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  • Possible breaking changes
    • Allow greater versions of:
      • catboost, lightgbm, xgboost
      • joblib, numpy
      • shap, swifter
      • matplotlib, tqdm, scipy
    • Most of the breaking changes in the libs above were due to deprecation of support to Python 3.5 and older versions.
    • Libraries depending on fklearn can still restrict the versions of the aforementioned libraries, keeping the previous behavior (e.g., xgboost<0.90).

1.24.0

06 Dec 18:25
aeaa36c
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  • New
    • Add causal curves summary
  • Bug fix
    • Set correct learner name for learners with column_duplicatable decorator

1.23.0

29 Oct 18:25
15db4df
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  • New
    • Add common causal evaluation techniques
    • Add methods to debias a dataframe with a treatment T and confounders X

1.22.2

01 Sep 20:32
73762db
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Bug fix

  • Remove cloudpickle from requirements
  • Remove cloudpickle from parallel_validator

1.22.0

09 Feb 17:03
aba8711
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  • Enhancement
    • Add verbose method to validator and parallel_validator
    • Add column_duplicator decorator to value_mapper
  • Bug Fix
    • Fix Spatial LC check
    • Fix circleci

1.21.0

02 Oct 15:10
5cc182f
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  • Enhancement
    • Now transformers can create a new column instead of replace the input
  • Bug Fix
    • Make requirements more flexible to cover the latest releases
    • split_evaluator_extractor now supports eval_name parameter
    • Fixed drop_first_column behaviour in onehot categorizer
  • New
    • Add learner to calibrate predictions based on a fairness metric
  • Documentation
    • Fixed docstrings for reverse_time_learning_curve_splitter and feature_importance_backward_selection

1.20.0

13 Jul 21:16
1f50d43
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  • Enhancement
    • Now Catboost learner is pickable

1.19.1

13 Jul 20:33
1777a4c
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  • Bug Fix
    • Be less restrictive with Numba requirements

1.19.0

17 Jun 22:48
11fa607
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  • Enhancement
    • Improve space_time_split_dataset performance