github tinkoff-ai/etna 1.7.0
etna 1.7.0

latest releases: 2.2.0, 2.1.0, 2.0.0...
2 years ago

Highlights:

  • New plots (a lot!): imputation, trend, change points, residuals, qq-plot, feature relevance, stl.
  • New regressors logic in TSDatasets, Transforms and Models
  • Added jupyter notebook with regressors example
  • Prediction intervals visualization in plot_forecast
  • Detrending could be polynomial
  • Added installation instruction for M1
  • Fixed TSDataset when plot method does not plot all required segments
  • VotingEnsemble allows to set weights of estimator as weights of pipelines

Full changelog:

Added

  • Regressors logic to TSDatasets init (#357)
  • FutureMixin into some transforms (#361)
  • Regressors updating in TSDataset transform loops (#374)
  • Regressors handling in TSDataset make_future and train_test_split (#447)
  • Prediction intervals visualization in plot_forecast (#538)
  • Add plot_imputation (#598)
  • Add plot_time_series_with_change_points function (#534)
  • Add plot_trend (#565)
  • Add find_change_points function (#521)
  • Add option day_number_in_year to DateFlagsTransform (#552)
  • Add plot_residuals (#539)
  • Add get_residuals (#597)
  • Create PerSegmentBaseModel, PerSegmentPredictionIntervalModel (#537)
  • Create MultiSegmentModel (#551)
  • Add qq_plot (#604)
  • Add regressors example notebook (#577)
  • Create EnsembleMixin (#574)
  • Add option season_number to DateFlagsTransform (#567)
  • Create BasePipeline, add prediction intervals to all the pipelines, move parameter n_fold to forecast (#578)
  • Add stl_plot (#575)
  • Add plot_features_relevance (#579)
  • Add community section to README.md (#580)
  • Create AbstaractPipeline (#573)
  • Option "auto" to weights parameter of VotingEnsemble, enables to use feature importance as weights of base estimators (https://github.com/tinkoff-ai/etna/pull/587[](https://github.com/tinkoff-ai/etna/releases/edit/1.7.0#changed-1))

Changed

  • Change the way ProphetModel works with regressors (#383)
  • Change the way SARIMAXModel works with regressors (#380)
  • Change the way Sklearn models works with regressors (#440)
  • Change the way FeatureSelectionTransform works with regressors, rename variables replacing the "regressor" to "feature" (#522)
  • Add table option to ConsoleLogger (#544)
  • Installation instruction (#526)
  • Update plot_forecast for multi-forecast mode (#584)
  • Trainer kwargs for deep models (#540)
  • Update CONTRIBUTING.md (#536)
  • Rename _CatBoostModel, _HoltWintersModel, _SklearnModel (#543)
  • Add logging to TSDataset.make_future, log repr of transform instead of class name (#555)
  • Rename _SARIMAXModel and _ProphetModel, make SARIMAXModel and ProphetModel inherit from PerSegmentPredictionIntervalModel (#549)
  • Update get_started section in README (#569)
  • Make detrending polynomial (#566)
  • Update documentation about transforms that generate regressors, update examples with them (#572)
  • Fix that segment is string (#602)
  • Make LabelEncoderTransform and OneHotEncoderTransform multi-segment (https://github.com/tinkoff-ai/etna/pull/554[](https://github.com/tinkoff-ai/etna/releases/edit/1.7.0#fixed-1))

Fixed

  • Fix TSDataset._update_regressors logic removing the regressors (#489)
  • Fix TSDataset.info, TSDataset.describe methods (#519)
  • Fix regressors handling for OneHotEncoderTransform and HolidayTransform (#518)
  • Fix wandb summary issue with custom plots (#535)
  • Small notebook fixes (#595)
  • Fix import Literal in plotters (#558)
  • Fix plot method bug when plot method does not plot all required segments (#596)
  • Fix dependencies for ARM (#599)
  • [BUG] nn models make forecast without inverse_transform (#541)

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