| Name | sklearn-utilities JSON |
| Version |
0.5.12
JSON |
| download |
| home_page | None |
| Summary | Utilities for scikit-learn. |
| upload_time | 2025-01-29 09:30:34 |
| maintainer | None |
| docs_url | None |
| author | 34j |
| requires_python | <3.13,>=3.9 |
| license | MIT |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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# Sklearn Utilities
<p align="center">
<a href="https://github.com/34j/sklearn-utilities/actions/workflows/ci.yml?query=branch%3Amain">
<img src="https://img.shields.io/github/actions/workflow/status/34j/sklearn-utilities/ci.yml?branch=main&label=CI&logo=github&style=flat-square" alt="CI Status" >
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<a href="https://sklearn-utilities.readthedocs.io">
<img src="https://img.shields.io/readthedocs/sklearn-utilities.svg?logo=read-the-docs&logoColor=fff&style=flat-square" alt="Documentation Status">
</a>
<a href="https://codecov.io/gh/34j/sklearn-utilities">
<img src="https://img.shields.io/codecov/c/github/34j/sklearn-utilities.svg?logo=codecov&logoColor=fff&style=flat-square" alt="Test coverage percentage">
</a>
</p>
<p align="center">
<a href="https://python-poetry.org/">
<img src="https://img.shields.io/badge/packaging-poetry-299bd7?style=flat-square&logo=data:image/png;base64,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" alt="Poetry">
</a>
<a href="https://github.com/ambv/black">
<img src="https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square" alt="black">
</a>
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<a href="https://pypi.org/project/sklearn-utilities/">
<img src="https://img.shields.io/pypi/v/sklearn-utilities.svg?logo=python&logoColor=fff&style=flat-square" alt="PyPI Version">
</a>
<img src="https://img.shields.io/pypi/pyversions/sklearn-utilities.svg?style=flat-square&logo=python&logoColor=fff" alt="Supported Python versions">
<img src="https://img.shields.io/pypi/l/sklearn-utilities.svg?style=flat-square" alt="License">
</p>
Utilities for scikit-learn.
## Installation
Install this via pip (or your favourite package manager):
```shell
pip install sklearn-utilities
```
## API
See [Docs](https://sklearn-utilities.readthedocs.io/en/latest/sklearn_utilities.html) for more information.
- `EstimatorWrapperBase`: base class for wrappers. Redirects all attributes which are not in the wrapper to the wrapped estimator.
- `DataFrameWrapper`: tries to convert every estimator output to a pandas DataFrame or Series.
- `FeatureUnionPandas`: a `FeatureUnion` that works with pandas DataFrames.
- `IncludedColumnTransformerPandas`, `ExcludedColumnTransformerPandas`: select columns by name.
- `AppendPredictionToX`: appends the prediction of y to X.
- `AppendXPredictionToX`: appends the prediction of X to X.
- `DropByNoisePrediction`: drops columns which has high importance in predicting noise.
- `DropMissingColumns`: drops columns with missing values above a threshold.
- `DropMissingRowsY`: drops rows with missing values in y. Use `feature_engine.DropMissingData` for X.
- `IntersectXY`: drops rows where the index of X and y do not intersect. Use with `feature_engine.DropMissingData`.
- `ReindexMissingColumns`: reindexes columns of X in `transform()` to match the columns of X in `fit()`.
- `ReportNonFinite`: reports non-finite values in X and/or y.
- `IdTransformer`: a transformer that does nothing.
- `RecursiveFitSubtractRegressor`: a regressor that recursively fits a regressor and subtracts the prediction from the target.
- `SmartMultioutputEstimator`: a `MultiOutputEstimator` that supports tuple of arrays in `predict()` and supports pandas `Series` and `DataFrame`.
- `until_event()`, `since_event()`: calculates the time since or until events (`Series[bool]`)
- `ComposeVarEstimator`: composes mean and std/var estimators.
- `DummyRegressorVar`: `DummyRegressor` that returns 1.0 for std/var.
- `TransformedTargetRegressorVar`: `TransformedTargetRegressor` with std/var support.
- `StandardScalerVar`: `StandardScaler` with std/var support.
- `EvalSetWrapper`, `CatBoostProgressBarWrapper`: wrapper that passes `eval_set` to `fit()` using `train_test_split()`, mainly for `CatBoost`. The latter shows progress bar (using `tqdm`) as well. Useful for early stopping. For LightGBM, see [`lightgbm-callbacks`](https://github.com/34j/lightgbm-callbacks).
### `sklearn_utilities.dataset`
- `add_missing_values()`: adds missing values to a dataset.
### `sklearn_utilities.torch`
- `PCATorch`: faster PCA using PyTorch with GPU support.
#### `sklearn_utilities.torch.skorch`
- `SkorchReshaper`, `SkorchCNNReshaper`: reshapes X and y for `nn.Linear` and `nn.Conv1d/2d` respectively. (For `nn.Conv2d`, uses `np.sliding_window_view()`.)
- `AllowNaN`: wraps a loss module and assign 0 to y and y_hat for indices where y contains NaN in `forward()`..
## See also
- [ml-tooling/best-of-ml-python](https://github.com/ml-tooling/best-of-ml-python)
## Contributors ✨
Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
<!-- prettier-ignore-start -->
<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
<!-- markdownlint-disable -->
<!-- markdownlint-enable -->
<!-- ALL-CONTRIBUTORS-LIST:END -->
<!-- prettier-ignore-end -->
This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!
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"description": "# Sklearn Utilities\n\n<p align=\"center\">\n <a href=\"https://github.com/34j/sklearn-utilities/actions/workflows/ci.yml?query=branch%3Amain\">\n <img src=\"https://img.shields.io/github/actions/workflow/status/34j/sklearn-utilities/ci.yml?branch=main&label=CI&logo=github&style=flat-square\" alt=\"CI Status\" >\n </a>\n <a href=\"https://sklearn-utilities.readthedocs.io\">\n <img src=\"https://img.shields.io/readthedocs/sklearn-utilities.svg?logo=read-the-docs&logoColor=fff&style=flat-square\" alt=\"Documentation Status\">\n </a>\n <a href=\"https://codecov.io/gh/34j/sklearn-utilities\">\n <img src=\"https://img.shields.io/codecov/c/github/34j/sklearn-utilities.svg?logo=codecov&logoColor=fff&style=flat-square\" alt=\"Test coverage percentage\">\n </a>\n</p>\n<p align=\"center\">\n <a href=\"https://python-poetry.org/\">\n <img src=\"https://img.shields.io/badge/packaging-poetry-299bd7?style=flat-square&logo=data:image/png;base64,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\" alt=\"Poetry\">\n </a>\n <a href=\"https://github.com/ambv/black\">\n <img src=\"https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square\" alt=\"black\">\n </a>\n <a href=\"https://github.com/pre-commit/pre-commit\">\n <img src=\"https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white&style=flat-square\" alt=\"pre-commit\">\n </a>\n</p>\n<p align=\"center\">\n <a href=\"https://pypi.org/project/sklearn-utilities/\">\n <img src=\"https://img.shields.io/pypi/v/sklearn-utilities.svg?logo=python&logoColor=fff&style=flat-square\" alt=\"PyPI Version\">\n </a>\n <img src=\"https://img.shields.io/pypi/pyversions/sklearn-utilities.svg?style=flat-square&logo=python&logoColor=fff\" alt=\"Supported Python versions\">\n <img src=\"https://img.shields.io/pypi/l/sklearn-utilities.svg?style=flat-square\" alt=\"License\">\n</p>\n\nUtilities for scikit-learn.\n\n## Installation\n\nInstall this via pip (or your favourite package manager):\n\n```shell\npip install sklearn-utilities\n```\n\n## API\n\nSee [Docs](https://sklearn-utilities.readthedocs.io/en/latest/sklearn_utilities.html) for more information.\n\n- `EstimatorWrapperBase`: base class for wrappers. 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