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Release 2.4.0 #198

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Dec 15, 2023
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Release 2.4.0 #198

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42 changes: 20 additions & 22 deletions CHANGELOG.md
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Expand Up @@ -5,19 +5,9 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).


## Unreleased
### Added
- Add params_to_tune for DeepStateModel ([#115](https://github.com/etna-team/etna/issues/115))
-
-
- Handle new functionality for prediction intervals in the `plot_forecast` ([#130](https://github.com/etna-team/etna/pull/130))
- Add `get_historical_forecasts` to pipelines for forecast estimation at each fold on the historical dataset ([#143](https://github.com/etna-team/etna/pull/143))
- `ConformalPredictionIntervals` method for prediction intervals estimation ([#152](https://github.com/etna-team/etna/pull/152))
- Add DeepARNativeModel ([#114](https://github.com/etna-team/etna/pull/114))
- `EmpiricalPredictionIntervals` method for prediction intervals estimation ([#173](https://github.com/etna-team/etna/pull/173))
- Prediction intervals tutorial notebook ([#189](https://github.com/etna-team/etna/pull/189))
-
-
-
-
-
Expand All @@ -35,11 +25,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
-

### Changed
- Change warning condition on loading object saved under different library version ([#31](https://github.com/etna-team/etna/issues/31))
-
-
-
-
-
-
-
Expand All @@ -58,12 +43,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

### Fixed
-
- Speed up segment column creation in `TSDataset.to_hierarchical_dataset` ([#194](https://github.com/etna-team/etna/pull/194))
- Speed up `BasePipeline._validate_backtest_dataset` ([#194](https://github.com/etna-team/etna/pull/194))
- Speed up `datasets.utils.duplicate_data` ([#194](https://github.com/etna-team/etna/pull/194))
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-
-
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Expand All @@ -77,6 +56,25 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
-
-
-
-

## [2.4.0] - 2023-12-15
### Added
- Add `params_to_tune` for `DeepStateModel` ([#115](https://github.com/etna-team/etna/issues/115))
- Handle new functionality for prediction intervals in the `plot_forecast` ([#130](https://github.com/etna-team/etna/pull/130))
- Add `get_historical_forecasts` to pipelines for forecast estimation at each fold on the historical dataset ([#143](https://github.com/etna-team/etna/pull/143))
- `ConformalPredictionIntervals` method for prediction intervals estimation ([#152](https://github.com/etna-team/etna/pull/152))
- Add `DeepARNativeModel` ([#114](https://github.com/etna-team/etna/pull/114))
- `EmpiricalPredictionIntervals` method for prediction intervals estimation ([#173](https://github.com/etna-team/etna/pull/173))
- Prediction intervals tutorial notebook ([#189](https://github.com/etna-team/etna/pull/189))

### Changed
- Change warning condition on loading object saved under different library version ([#31](https://github.com/etna-team/etna/issues/31))

### Fixed
- Speed up segment column creation in `TSDataset.to_hierarchical_dataset` ([#194](https://github.com/etna-team/etna/pull/194))
- Speed up `BasePipeline._validate_backtest_dataset` ([#194](https://github.com/etna-team/etna/pull/194))
- Speed up `datasets.utils.duplicate_data` ([#194](https://github.com/etna-team/etna/pull/194))

## [2.3.0] - 2023-10-24
### Added
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9 changes: 7 additions & 2 deletions docs/source/_static/switcher.json
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Expand Up @@ -5,10 +5,15 @@
"url": "https://docs.etna.ai/latest/"
},
{
"name": "2.3.0 (stable)",
"version": "2.3.0",
"name": "2.4.0 (stable)",
"version": "2.4.0",
"url": "https://docs.etna.ai/stable/"
},
{
"name": "2.3.0",
"version": "2.3.0",
"url": "https://docs.etna.ai/2.3.0/"
},
{
"name": "2.2.0",
"version": "2.2.0",
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2 changes: 1 addition & 1 deletion pyproject.toml
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@@ -1,6 +1,6 @@
[tool.poetry]
name = "etna"
version = "2.3.0"
version = "2.4.0"
repository = "https://github.com/etna-team/etna"
readme = "README.md"
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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