CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

Added

• Lambda transform (#762)
• Tests on in-sample, out-sample predictions with gap for all models (#785)

Changed

• Add columns and mode parameters in plot_correlation_matrix (#726)
• Add CatBoostPerSegmentModel and CatBoostMultiSegmentModel classes, deprecate CatBoostModelPerSegment and CatBoostModelMultiSegment (#779)
• Make LagTransform, LogTransform, AddConstTransform vectorized (#756)
• Update poetry.core version (#780)
• Make native prediction intervals for DeepAR (#761)
• Make native prediction intervals for TFTModel (#770)
• Test cases for testing inference of models (#794)

Fixed

• Fix missing prophet in docker images (#767)
• Add known_future parameter to CLI (#758)
• FutureWarning: The frame.append method is deprecated. Use pandas.concat instead (#764)
• Correct ordering if multi-index in backtest (#771)
• Github actions cache issue with poetry update (#778)

[1.10.0] - 2022-06-12

Added

• Add Sign metric (#730)
• Add AutoARIMA model (#679)
• Add parameters start, end to some eda methods (#665)
• Add BATS and TBATS model adapters (#678)
• Jupyter extension for black (#742)

Changed

• Change color of lines in plot_anomalies and plot_clusters, add grid to all plots, make trend line thicker in plot_trend (#705)
• Change format of holidays for holiday_plot (#708)
• Make feature selection transforms return columns in inverse_transform(#688)
• Add xticks parameter for plot_periodogram, clip frequencies to be >= 1 (#706)
• Make TSDataset method to_dataset work with copy of the passed dataframe (#741)

Fixed

• Fix bug when ts.plot does not save figure (#714)
• Fix bug in plot_clusters (#675)
• Fix bugs and documentation for cross_corr_plot (#691)
• Fix bugs and documentation for plot_backtest and plot_backtest_interactive (#700)
• Make STLTransform to work with NaNs at the beginning (#736)
• Fix tiny prediction intervals (#722)
• Fix deepcopy issue for fitted deepmodel (#735)
• Fix making backtest if all segments start with NaNs (#728)
• Fix logging issues with backtest while emp intervals using (#747)

[1.9.0] - 2022-05-17

Added

• Add plot_metric_per_segment (#658)
• Add metric_per_segment_distribution_plot (#666)

Changed

• Remove parameter normalize in linear models (#686)

Fixed

• Add missed forecast_params in forecast CLI method (#671)
• Add _per_segment_average method to the Metric class (#684)
• Fix get_statistics_relevance_table working with NaNs and categoricals (#672)
• Fix bugs and documentation for stl_plot (#685)
• Fix cuda docker images (#694])

[1.8.0] - 2022-04-28

Added

• Width and Coverage metrics for prediction intervals (#638)
• Masked backtest (#613)
• Add seasonal_plot (#628)
• Add plot_periodogram (#606)
• Add support of quantiles in backtest (#652)
• Add prediction_actual_scatter_plot (#610)
• Add plot_holidays (#624)
• Add instruction about documentation formatting to contribution guide (#648)
• Seasonal strategy in TimeSeriesImputerTransform (#639)

Changed

• Add logging to Metric.__call__ (#643)
• Add in_column to plot_anomalies, plot_anomalies_interactive (#618)
• Add logging to TSDataset.inverse_transform (#642)

Fixed

• Passing non default params for default models STLTransform (#641)
• Fixed bug in SARIMAX model with horizon=1 (#637)
• Fixed bug in models get_model method (#623)
• Fixed unsafe comparison in plots (#611)
• Fixed plot_trend does not work with Linear and TheilSen transforms (#617)
• Improve computation time for rolling window statistics (#625)
• Don't fill first timestamps in TimeSeriesImputerTransform (#634)
• Fix documentation formatting (#636)
• Fix bug with exog features in AutoRegressivePipeline (#647)
• Fix missed dependencies (#656)
• Fix custom_transform_and_model notebook (#651)
• Fix MyBinder bug with dependencies (#650)

[1.7.0] - 2022-03-16

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 (#587)

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 (#554)

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)

[1.6.3] - 2022-02-14

Fixed

• Fixed adding unnecessary lag=1 in statistics (#523)
• Fixed wrong MeanTransform behaviour when using alpha parameter (#523)
• Fix processing add_noise=True parameter in datasets generation (#520)
• Fix scipy version (#525)

[1.6.2] - 2022-02-09

Added

• Holt-Winters', Holt and exponential smoothing models (#502)

Fixed

• Bug with exog features in DifferencingTransform.inverse_transform (#503)

[1.6.1] - 2022-02-03

Added

• Allow choosing start and end in TSDataset.plot method (488)

Changed

• Make TSDataset.to_flatten faster (#475)
• Allow logger percentile metric aggregation to work with NaNs (#483)

Fixed

• Can't make forecasting with pipelines, data with nans, and Imputers (#473)

[1.6.0] - 2022-01-28

Added

• Method TSDataset.info (#409)
• DifferencingTransform (#414)
• OneHotEncoderTransform and LabelEncoderTransform (#431)
• MADTransform (#441)
• MRMRFeatureSelectionTransform (#439)
• Possibility to change metric representation in backtest using Metric.name (#454)
• Warning section in documentation about look-ahead bias (#464)
• Parameter figsize to all the plotters #465

Changed

• Change method TSDataset.describe (#409)
• Group Transforms according to their impact (#420)
• Change the way LagTransform, DateFlagsTransform and TimeFlagsTransform generate column names (#421)
• Clarify the behaviour of TimeSeriesImputerTransform in case of all NaN values (#427)
• Fixed bug in title in sample_acf_plot method (#432)
• Pytorch-forecasting and sklearn version update + some pytroch transform API changing (#445)

Fixed

• Add relevance_params in GaleShapleyFeatureSelectionTransform (#410)
• Docs for statistics transforms (#441)
• Handling NaNs in trend transforms (#456)
• Logger fails with StackingEnsemble (#460)
• SARIMAX parameters fix (#459)
• [BUG] Check pytorch-forecasting models with freq > "1D" (#463)

[1.5.0] - 2021-12-24

Added

• Holiday Transform (#359)
• S3FileLogger and LocalFileLogger (#372)
• Parameter changepoint_prior_scale to ProphetModel (#408)

Changed

• Set strict_optional = True for mypy (#381)
• Move checking the series endings to make_future step (#413)

Fixed

• Sarimax bug in future prediction with quantiles (#391)
• Catboost version too high (#394)
• Add sorting of classes in left bar in docs (#397)
• nn notebook in docs (#396)
• SklearnTransform column name generation (#398)
• Inverse transform doesn't affect quantiles (#395)

[1.4.2] - 2021-12-09

Fixed

• Docs generation for neural networks

[1.4.1] - 2021-12-09

Changed

• Speed up _check_regressors and _merge_exog (#360)

Fixed

• Model, PerSegmentModel, PerSegmentWrapper imports (#362)
• Docs generation (#363)
• Fixed work of get_anomalies_density with constant series (#334)

[1.4.0] - 2021-12-03

Added

• ACF plot (#318)

Changed

• Add ts.inverse_transform as final step at Pipeline.fit method (#316)
• Make test_ts optional in plot_forecast (#321)
• Speed up inference for multisegment regression models (#333)
• Speed up Pipeline._get_backtest_forecasts (#336)
• Speed up SegmentEncoderTransform (#331)
• Wandb Logger does not work unless pytorch is installed (#340)

Fixed

• Get rid of lambda in DensityOutliersTransform and get_anomalies_density (#341)
• Fixed import in transforms (#349)
• Pickle DTWClustering (#350)

Removed

• Remove TimeSeriesCrossValidation (#337)

[1.3.3] - 2021-11-24

Added

• RelevanceTable returns rank (#268)
• GaleShapleyFeatureSelectionTransform (#284)
• FilterFeaturesTransform (#277)
• Spell checking for source code and md files (#303)
• ResampleWithDistributionTransform (#296)
• Add function to duplicate exogenous data (#305)
• FourierTransform (#306)

Changed

• Rename confidence interval to prediction interval, start working with quantiles instead of interval_width (#285)
• Changed format of forecast and test dataframes in WandbLogger (#309)

Fixed

[1.3.2] - 2021-11-18

Changed

• Add sum for omegaconf resolvers (#300)

[1.3.1] - 2021-11-12

Changed

• Delete restriction on version of pandas (#274)

[1.3.0] - 2021-11-12

Added

• Backtest cli (#223, #259)
• TreeFeatureSelectionTransform (#229)
• Feature relevance table calculation using tsfresh (#227, #249)
• Method to_flatten to TSDataset (#241
• Out_column parameter to not inplace transforms(#211)
• omegaconf config parser in cli (#258)
• Feature relevance table calculation using feature importance (#261)
• MeanSegmentEncoderTransform (#265)

Changed

• Add possibility to set custom in_column for ConfidenceIntervalOutliersTransform (#240)
• Make in_column the first argument in every transform (#247)
• Update mypy checking and fix issues with it (#248)
• Add histogram method in outliers notebook (#252)
• Joblib parameters for backtest and ensembles (#253)
• Replace cycle over segments with vectorized expression in TSDataset._check_endings (#264)

Fixed

• Fixed broken links in docs command section (#223)
• Fix default value for TSDataset.tail (#245)
• Fix raising warning on fitting SklearnModel on dataset categorical columns (#250)
• Fix working TSDataset.make_future with empty exog values (#244)
• Fix issue with aggregate_metrics=True for ConsoleLogger and WandbLogger (#254)
• Fix binder requirements to work with optional dependencies (#257)

[1.2.0] - 2021-10-27

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)
• Simplify TSDataset.train_test_split method by allowing to pass not all values (#191)
• Confidence interval anomalies detection to EDA (#182)
• ConfidenceIntervalOutliersTransform (#196)
• Add 'in_column' parameter to get_anomalies methods(#199)
• Clustering notebook (#152)
• StackingEnsemble (#195)
• Add AutoRegressivePipeline (#209)
• Ensembles notebook (#218)
• Function plot_backtest_interactive (#225)
• Confidence intervals in Pipeline (#221)

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)
• Add badges to all example notebooks (#220)
• Update backtest notebook by adding Pipeline.backtest (222)

Fixed

• Set default value of TSDataset.head method (#170)
• Categorical and fillna issues with pandas >=1.2 (#190)
• Fix TSDataset.to_dataset method sorting bug (#183)
• Undefined behaviour of DataFrame.loc[:, pd.IndexSlice[:, ["a", "b"]]] between 1.1.* and >= 1.2 (#188)
• Fix typo in word "length" in get_segment_sequence_anomalies,get_sequence_anomalies,SAXOutliersTransform arguments (#212)
• Make possible to send backtest plots with many segments (#225)

[1.1.3] - 2021-10-08

Fixed

• Limit version of pandas by 1.2 (excluding) (#163)

[1.1.2] - 2021-10-08

Changed

• SklearnTransform out column names (#99)
• Update EDA notebook (#96)
• Add 'regressor_' prefix to output columns of LagTransform, DateFlagsTransform, SpecialDaysTransform, SegmentEncoderTransform

Fixed

• Add more obvious Exception Error for forecasting with unfitted model (#102)
• Fix bug with hardcoded frequency in PytorchForecastingTransform (#107)
• Bug with inverse_transform method of TimeSeriesImputerTransform (#148)

[1.1.1] - 2021-09-23

Fixed

• Documentation build workflow (#85)

[1.1.0] - 2021-09-23

Added

• MedianOutliersTransform, DensityOutliersTransform (#30)
• Issues and Pull Request templates
• TSDataset checks (#24, #20)\
• Pytorch-Forecasting models (#29)
• SARIMAX model (#10)
• Logging, including ConsoleLogger (#46)
• Correlation heatmap plotter (#77)

Changed

• Backtest is fully parallel
• New default hyperparameters for CatBoost
• Add 'regressor_' prefix to output columns of LagTransform, DateFlagsTransform, SpecialDaysTransform, SegmentEncoderTransform

Fixed

• Documentation fixes (#55, #53, #52)
• Solved warning in LogTransform and AddConstantTransform (#26)
• Regressors do not have enough history bug (#35)
• make_future(1) and make_future(2) bug
• Fix working with 'cap' and 'floor' features in Prophet model (#62)
• Fix saving init params for SARIMAXModel (#81)
• Imports of nn models, PytorchForecastingTransform and Transform (#80)

[1.0.0] - 2021-09-05

Added

• Models
  • CatBoost
  • Prophet
  • Seasonal Moving Average
  • Naive
  • Linear
• Transforms
  • Rolling statistics
  • Trend removal
  • Segment encoder
  • Datetime flags
  • Sklearn's scalers (MinMax, Robust, MinMaxAbs, Standard, MaxAbs)
  • BoxCox, YeoJohnson, LogTransform
  • Lag operator
  • NaN imputer
• TimeSeriesCrossValidation
• Time Series Dataset (TSDataset)
• Playground datasets generation (AR, constant, periodic, from pattern)
• Metrics (MAE, MAPE, SMAPE, MedAE, MSE, MSLE, R^2)
• EDA methods
  • Outliers detection
  • PACF plot
  • Cross correlation plot
  • Distribution plot
  • Anomalies (Outliers) plot
  • Backtest (CrossValidation) plot
  • Forecast plot