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0.0.3 - 2019-03-21

base

  • Calling fit_one now returns the calling instance, not the out-of-fold prediction/transform; fit_predict_one, fit_predict_proba_one, and fit_transform_one are available to reproduce the previous behavior.
  • Binary classifiers now output a dict with probabilities for False and True when calling predict_proba_one, which solves the interface issues of having multi-class classifiers do binary classification.

compat

compose

  • Added compose.BoxCoxTransformRegressor.
  • Added compose.TargetModifierRegressor.

datasets

  • Added datasets.fetch_restaurants.
  • Added datasets.load_airline.

dist

  • Added dist.Multinomial.
  • Added dist.Normal.

ensemble

feature_extraction

  • Added feature_extraction.TargetGroupBy.

impute

  • Added impute.CategoricalImputer.

linear_model

  • Added linear_model.FMRegressor.
  • Removed all the passive-aggressive estimators.

metrics

model_selection

  • model_selection.online_score can now be passed a metrics.Metric instead of an sklearn metric; it also checks that the provided metric can be used with the accompanying model.

naive_bayes

optim

  • Added optim.PassiveAggressiveI.
  • Added optim.PassiveAggressiveII.

preprocessing

  • Added preprocessing.Discarder.
  • Added preprocessing.PolynomialExtender.
  • Added preprocessing.FuncTransformer.

reco

  • Added reco.SVD.

stats

stream

tree

  • Added tree.MondrianTreeClassifier.
  • Added tree.MondrianTreeRegressor.