0.1.0 - 2019-05-08
base
- Removed the
fit_predict_one estimator method.
- Removed the
fit_predict_proba_one estimator method.
- Removed the
fit_transform_one estimator method.
compat
- Added
compat.convert_sklearn_to_river.
compat.convert_river_to_sklearn now returns an sklearn.pipeline.Pipeline when provided with a compose.Pipeline.
compose
- Added
compose.Discard.
- Added
compose.Select.
- Added
compose.SplitRegressor.
- The
draw method of compose.Pipeline now works properly for arbitrary amounts of nesting, including multiple nested compose.FeatureUnion.
datasets
- Added
datasets.fetch_electricity.
dummy
- Added
dummy.NoChangeClassifier.
- Added
dummy.PriorClassifier.
- Added
dummy.StatisticRegressor.
- Added
feature_extraction.Differ.
- Renamed
feature_extraction.GroupBy to feature_extraction.Agg.
- Renamed
feature_extraction.TargetGroupBy to feature_extraction.TargetAgg.
feature_selection
- Added
feature_selection.SelectKBest.
- Added
feature_selection.VarianceThreshold.
impute
- Added
impute.StatImputer.
- Removed
impute.CategoricalImputer.
- Removed
impute.NumericImputer.
linear_model
- Added
linear_model.PAClassifier.
- Added
linear_model.PARegressor.
- Added
linear_model.SoftmaxRegression.
metrics
- Added
metrics.ConfusionMatrix.
- Added
metrics.CrossEntropy.
- Added
metrics.MacroF1.
- Added
metrics.MacroPrecision.
- Added
metrics.MacroRecall.
- Added
metrics.MicroF1.
- Added
metrics.MicroPrecision.
- Added
metrics.MicroRecall.
- Each metric now has a
bigger_is_better property to indicate if a high value is better than a low one or not.
optim
- Added
optim.OptimalLR.
- Added
optim.CrossEntropy.
- Removed
optim.PassiveAggressiveI.
- Removed
optim.PassiveAggressiveII.
preprocessing
- Removed
preprocessing.Discarder.
- Added
on and sparse parameters to preprocessing.OneHotEncoder.
stats
- Added
stats.Covariance.
- Added
stats.PearsonCorrelation.
- Added
stats.SmoothMean.
utils
- Added
utils.check_estimator.
- Added
utils.Histogram.
- Added
utils.SortedWindow.
- Added
utils.Window.