etna 1.4.1

• Made Model, PerSegmentModel, PerSegmentWrapper imports more convenient
• Docs now have all neural networks models
• Speed up _check_regressors and _merge_exog

etna 1.4.0

Hi!
In this release we have focused on speed and bug fixes.

Added

• ACF plot

Changed

• Add ts.inverse_transform as final step at Pipeline.fit method
• Make test_ts optional in plot_forecast
• Speed up inference for multisegment regression models
• Speed up Pipeline._get_backtest_forecasts
• Speed up SegmentEncoderTransform
• Wandb Logger does not work unless pytorch is installed

Fixed

• Get rid of lambda in DensityOutliersTransform and get_anomalies_density
• Fixed import in transforms
• Pickle DTWClustering

Removed

• Remove TimeSeriesCrossValidation

etna 1.3.3

Added:

• RelevanceTable can return rank
• GaleShapleyFeatureSelectionTransform based one Gale-Shapley algorithm
• FilterFeaturesTransform for selecting features from TSDataset while feature engineering
• ResampleWithDistributionTransform helps to resample features according to the other feature distribution
• Spell checks in ci

Changed:

• Rename confidence interval to prediction interval, start working with quantiles instead of interval_width
• Changed format of forecast and test dataframes in WandbLogger

etna 1.3.2

Minor addition:

• Add sum for omegaconf resolvers

etna 1.3.1

Also we remove restriction on version of pandas

etna 1.3.0

We are happy to announce 1.3.0 version of the etna library!

We focused on making etna even more user friendly as well as added new features.

We have added:

• CLI for backtesting
• MeanSegmentEncoderTransform
• Several feature relevance algorithms
• TreeFeatureSelectionTransform

We have fixed:

• Bugs in loggers when aggregate_metrics=True
• Bug when TSDataset did not create future if exogenous data has empty future
• links in CLI documentation

:bomb: PRE-release 1.3.0-alpha.0

In progress...

In this prerelease we are testing optional dependencies. Be careful!

Docs available at https://unstable--etna-docs.netlify.app

etna 1.2.0

Boom! Huge update!

Added

• Even more documentation
• Even more Jupyter Notebooks with examples
• Pipeline class, helps unite models and transforms
• Ensemble classes, helps unite models
• AutoRegressivePipeline
• Add confidence intervals to pipelines, models and transforms
• Add new Transforms
• Add clustering methods

Changed

• backtest moved to Pipeline class

Fixed

• pandas bugs
• TSDataset.to_dataset bug

More in our Changelog

:bomb: PRE-release 1.2.0-alpha.1

Fix bug in TSDataset

:bomb: PRE-release 1.2.0-alpha.0

Added

• BinsegTrendTransform, ChangePointsTrendTransform (#87)
• Interactive plot for anomalies (#95)
• Examples to TSDataset methods with doctest (#92)
• WandbLogger (#71)
• Pipeline (#78)
• Sequence anomalies (#96), Histogram anomalies (#79)
• 'is_weekend' feature in DateFlagsTransform (#101)
• Documentation example for models and note about inplace nature of forecast (#112)
• Property regressors to TSDataset (#82)
• Clustering (#110)
• Outliers notebook (#123))
• Method inverse_transform in TimeSeriesImputerTransform (#135)
• VotingEnsemble (#150)
• Forecast command for cli (#133)
• MyPy checks in CI/CD and lint commands (#39)
• TrendTransform (#139)
• Running notebooks in ci (#134)
• Cluster plotter to EDA (#169)
• Pipeline.backtest method (#161, #192)
• STLTransform class (#158)
• NN_examples notebook (#159)
• Example for ProphetModel (#178)
• Instruction notebook for custom model and transform creation (#180)
• Add inverse_transform in *OutliersTransform (#160)
• Examples for CatBoostModelMultiSegment and CatBoostModelPerSegment (#181)

Changed

• Delete offset from WindowStatisticsTransform (#111)
• Add Pipeline example in Get started notebook (#115)
• Internal implementation of BinsegTrendTransform (#141)
• Colorebar scaling in Correlation heatmap plotter (#143)
• Add Correlation heatmap in EDA notebook (#144)
• Add __repr__ for Pipeline (#151)
• Defined random state for every test cases (#155)
• Add confidence intervals to Prophet (#153)
• Add confidence intervals to SARIMA (#172)

Fixed

• Set default value of TSDataset.head method (#170)
• Categorical and fillna issues with pandas >=1.2 (#190)