Version 0.3.0

  • Deployed: Monday, August 05, 2019
  • Contributors: Soledad Galli.
Major Changes:
  • New: the RandomSampleImputer now has the option to set one seed for batch imputation or set a seed observation per observations based on 1 or more additional numerical variables for that observation, which can be combined with multiplication or addition.
  • New: the YeoJohnsonTransfomer has been included to perform Yeo-Johnson transformation of numerical variables.
  • Renamed: the ExponentialTransformer is now called PowerTransformer.
  • Improved: the DecisionTreeDiscretiser now allows to provide a grid of parameters to tune the decision trees which is done with a GridSearchCV under the hood.
  • New: Extended documentation for all Feature-engine’s transformers.
  • New: Quickstart guide to jump on straight onto how to use Feature-engine.
  • New: Changelog to track what is new in Feature-engine.
  • Updated: new Jupyter notebooks with examples on how to use Feature-engine’s transformers.
Minor Changes:
  • Unified: dictionary attributes in transformers, which contain the transformation mappings, now end with _, for example binner_dict_.