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- Add `experimental` module with `TimeSeriesBinaryClassifier` and `PredictabilityAnalyzer` ([#985](https://github.com/tinkoff-ai/etna/pull/985))
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- Inference track results: add `predict` method to pipelines, teach some models to work with context, change hierarchy of base models, update notebook examples ([#979](https://github.com/tinkoff-ai/etna/pull/979))
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- Add `get_ruptures_regularization` into `experimental` module ([#1001](https://github.com/tinkoff-ai/etna/pull/1001))
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- Add example `classification` notebook for experimental classification feature ([#997](https://github.com/tinkoff-ai/etna/pull/997))
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### Changed
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- Change returned model in get_model of BATSModel, TBATSModel ([#987](https://github.com/tinkoff-ai/etna/pull/987))
- Change returned model in `get_model` of `HoltWintersModel`, `HoltModel`, `SimpleExpSmoothingModel` ([#986](https://github.com/tinkoff-ai/etna/pull/986))
description = "ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun."
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