diff --git a/.github/Pull_Request_template.md b/.github/Pull_Request_template.md index 8d554abb77..c79b8b8fa0 100644 --- a/.github/Pull_Request_template.md +++ b/.github/Pull_Request_template.md @@ -23,7 +23,7 @@ Checklist to comply with **before moving PR from draft**: - [ ] I have reviewed my changes thoroughly before submitting this pull request. - [ ] I have commented my code, particularly in hard-to-understand areas. - [ ] I have updated the documentation to reflect the changes or created a separate PR with update and provided its number in the description, if necessary. -- [ ] Git commit message contains an appropriate signed-off-by string _(see [CONTRIBUTING.md](https://github.com/intel/scikit-learn-intelex/blob/main/CONTRIBUTING.md#pull-requests) for details)_. +- [ ] Git commit message contains an appropriate signed-off-by string _(see [CONTRIBUTING.md](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/CONTRIBUTING.md#pull-requests) for details)_. - [ ] I have added a respective label(s) to PR if I have a permission for that. - [ ] I have resolved any merge conflicts that might occur with the base branch. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index ef1fd870d8..adf9503ed1 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -22,7 +22,7 @@ This document explains how to participate in project conversations, log bugs and ## Licensing -Intel(R) Extension for Scikit-learn uses the [Apache 2.0 License](https://github.com/intel/scikit-learn-intelex/blob/main/LICENSE). +Intel(R) Extension for Scikit-learn uses the [Apache 2.0 License](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/LICENSE). By contributing to the project, you agree to the license and copyright terms and release your own contributions under these terms. ## Pull Requests @@ -47,7 +47,7 @@ Continuous Integration (CI) testing is enabled for the repository. Your pull req ## Code Style -We use [black](https://black.readthedocs.io/en/stable/) version 24.1.1 and [isort](https://pycqa.github.io/isort/) version 5.13.2 formatters for Python* code. The line length is 90 characters; use default options otherwise. You can find the linter configuration in [.pyproject.toml](https://github.com/intel/scikit-learn-intelex/blob/main/pyproject.toml). +We use [black](https://black.readthedocs.io/en/stable/) version 24.1.1 and [isort](https://pycqa.github.io/isort/) version 5.13.2 formatters for Python* code. The line length is 90 characters; use default options otherwise. You can find the linter configuration in [.pyproject.toml](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/pyproject.toml). A GitHub* Action verifies if your changes comply with the output of the auto-formatting tools. diff --git a/INSTALL.md b/INSTALL.md index 72b04544cd..f05d7a4cb2 100755 --- a/INSTALL.md +++ b/INSTALL.md @@ -40,7 +40,7 @@ To install Intel(R) Extension for Scikit-learn*, use one of the following scenar ## Before You Begin -Check [System](https://intel.github.io/scikit-learn-intelex/latest/system-requirements.html) and [Memory](https://intel.github.io/scikit-learn-intelex/latest/memory-requirements.html) Requirements. +Check [System](https://uxlfoundation.github.io/scikit-learn-intelex/latest/system-requirements.html) and [Memory](https://uxlfoundation.github.io/scikit-learn-intelex/latest/memory-requirements.html) Requirements. ## Supported Configurations @@ -158,7 +158,7 @@ The build-process (using setup.py) happens in 4 stages: * cmake and pybind11 * A C++ compiler with C++11 support * Clang-Format -* [IntelĀ® oneAPI Data Analytics Library (oneDAL)](https://github.com/oneapi-src/oneDAL) version 2021.1 or later +* [IntelĀ® oneAPI Data Analytics Library (oneDAL)](https://github.com/uxlfoundation/oneDAL) version 2021.1 or later * You can use the pre-built `dal-devel` conda package from conda-forge channel * MPI (optional, needed for distributed mode) * You can use the pre-built `impi_rt` and `impi-devel` conda packages from conda-forge channel @@ -253,5 +253,5 @@ conda build . ## Next Steps -- [Learn what patching is and how to patch scikit-learn](https://intel.github.io/scikit-learn-intelex/latest/what-is-patching.html) -- [Start using scikit-learn-intelex](https://intel.github.io/scikit-learn-intelex/latest/quick-start.html) +- [Learn what patching is and how to patch scikit-learn](https://uxlfoundation.github.io/scikit-learn-intelex/latest/what-is-patching.html) +- [Start using scikit-learn-intelex](https://uxlfoundation.github.io/scikit-learn-intelex/latest/quick-start.html) diff --git a/README.md b/README.md index e6ac933e58..717a01a6e7 100755 --- a/README.md +++ b/README.md @@ -5,12 +5,12 @@

Speed up your scikit-learn applications for Intel(R) CPUs and GPUs across single- and multi-node configurations -[Releases](https://github.com/intel/scikit-learn-intelex/releases)   |   [Documentation](https://intel.github.io/scikit-learn-intelex/)   |   [Examples](https://github.com/intel/scikit-learn-intelex/tree/master/examples/notebooks)   |   [Support]()   |  [License](https://github.com/intel/scikit-learn-intelex/blob/master/LICENSE)    +[Releases](https://github.com/uxlfoundation/scikit-learn-intelex/releases)   |   [Documentation](https://uxlfoundation.github.io/scikit-learn-intelex/)   |   [Examples](https://github.com/uxlfoundation/scikit-learn-intelex/tree/master/examples/notebooks)   |   [Support]()   |  [License](https://github.com/uxlfoundation/scikit-learn-intelex/blob/master/LICENSE)    [![Build Status](https://dev.azure.com/daal/daal4py/_apis/build/status/CI?branchName=main)](https://dev.azure.com/daal/daal4py/_build/latest?definitionId=9&branchName=main) [![Coverity Scan Build Status](https://scan.coverity.com/projects/21716/badge.svg)](https://scan.coverity.com/projects/daal4py) -[![Join the community on GitHub Discussions](https://badgen.net/badge/join%20the%20discussion/on%20github/black?icon=github)](https://github.com/intel/scikit-learn-intelex/discussions) +[![Join the community on GitHub Discussions](https://badgen.net/badge/join%20the%20discussion/on%20github/black?icon=github)](https://github.com/uxlfoundation/scikit-learn-intelex/discussions) [![PyPI Version](https://img.shields.io/pypi/v/scikit-learn-intelex)](https://pypi.org/project/scikit-learn-intelex/) [![Conda Version](https://img.shields.io/conda/vn/conda-forge/scikit-learn-intelex)](https://anaconda.org/conda-forge/scikit-learn-intelex) [![python version](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue)](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue) @@ -39,7 +39,7 @@ Intel(R) Extension for Scikit-learn is also a part of [Intel(R) AI Tools](https: ## Acceleration -![](https://raw.githubusercontent.com/intel/scikit-learn-intelex/master/doc/sources/_static/scikit-learn-acceleration.PNG) +![](https://raw.githubusercontent.com/uxlfoundation/scikit-learn-intelex/master/doc/sources/_static/scikit-learn-acceleration.PNG) [Benchmarks code](https://github.com/IntelPython/scikit-learn_bench) @@ -74,7 +74,7 @@ Intel(R) Extension for Scikit-learn is also a part of [Intel(R) AI Tools](https: with config_context(target_offload="gpu:0"): clustering = DBSCAN(eps=3, min_samples=2).fit(X) ``` -:eyes: Check out available [notebooks](https://github.com/intel/scikit-learn-intelex/tree/master/examples/notebooks) for more examples. +:eyes: Check out available [notebooks](https://github.com/uxlfoundation/scikit-learn-intelex/tree/master/examples/notebooks) for more examples. ## Installation @@ -84,16 +84,16 @@ To install Intel(R) Extension for Scikit-learn, run: pip install scikit-learn-intelex ``` -See all installation instructions in the [Installation Guide](https://intel.github.io/scikit-learn-intelex/latest/installation.html). +See all installation instructions in the [Installation Guide](https://uxlfoundation.github.io/scikit-learn-intelex/latest/installation.html). ## Integration The software acceleration is achieved through patching. It means, replacing the stock scikit-learn algorithms with their optimized versions provided by the extension. -The patching only affects [supported algorithms and their parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html). +The patching only affects [supported algorithms and their parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html). You can still use not supported ones in your code, the package simply fallbacks into the stock version of scikit-learn. -> **_TIP:_** Enable [verbose mode](https://intel.github.io/scikit-learn-intelex/latest/verbose.html) to see which implementation of the algorithm is currently used. +> **_TIP:_** Enable [verbose mode](https://uxlfoundation.github.io/scikit-learn-intelex/latest/verbose.html) to see which implementation of the algorithm is currently used. To patch scikit-learn, you can: * Use the following command-line flag: @@ -106,32 +106,32 @@ To patch scikit-learn, you can: patch_sklearn() ``` -:eyes: Read about [other ways to patch scikit-learn](https://intel.github.io/scikit-learn-intelex/index.html#usage). +:eyes: Read about [other ways to patch scikit-learn](https://uxlfoundation.github.io/scikit-learn-intelex/index.html#usage). ## Documentation -* [Quick Start](https://intel.github.io/scikit-learn-intelex/latest/quick-start.html) -* [Documentation and Tutorials](https://intel.github.io/scikit-learn-intelex/latest/index.html) -* [Release Notes](https://github.com/intel/scikit-learn-intelex/releases) -* [Medium Blogs](https://intel.github.io/scikit-learn-intelex/latest/blogs.html) -* [Code of Conduct](https://github.com/intel/scikit-learn-intelex/blob/master/CODE_OF_CONDUCT.md) +* [Quick Start](https://uxlfoundation.github.io/scikit-learn-intelex/latest/quick-start.html) +* [Documentation and Tutorials](https://uxlfoundation.github.io/scikit-learn-intelex/latest/index.html) +* [Release Notes](https://github.com/uxlfoundation/scikit-learn-intelex/releases) +* [Medium Blogs](https://uxlfoundation.github.io/scikit-learn-intelex/latest/blogs.html) +* [Code of Conduct](https://github.com/uxlfoundation/scikit-learn-intelex/blob/master/CODE_OF_CONDUCT.md) ### daal4py and oneDAL The acceleration is achieved through the use of the Intel(R) oneAPI Data Analytics Library (oneDAL). Learn more: -- [About Intel(R) oneAPI Data Analytics Library](https://github.com/oneapi-src/oneDAL) -- [About daal4py](https://github.com/intel/scikit-learn-intelex/tree/main/daal4py) +- [About Intel(R) oneAPI Data Analytics Library](https://github.com/uxlfoundation/oneDAL) +- [About daal4py](https://github.com/uxlfoundation/scikit-learn-intelex/tree/main/daal4py) ## Samples & Examples -* [Examples](https://github.com/intel/scikit-learn-intelex/tree/master/examples/notebooks) -* [Samples](https://intel.github.io/scikit-learn-intelex/latest/samples.html) -* [Kaggle Kernels](https://intel.github.io/scikit-learn-intelex/latest/kaggle.html) +* [Examples](https://github.com/uxlfoundation/scikit-learn-intelex/tree/master/examples/notebooks) +* [Samples](https://uxlfoundation.github.io/scikit-learn-intelex/latest/samples.html) +* [Kaggle Kernels](https://uxlfoundation.github.io/scikit-learn-intelex/latest/kaggle.html) ## How to Contribute -We welcome community contributions, check our [Contributing Guidelines](https://github.com/intel/scikit-learn-intelex/blob/master/CONTRIBUTING.md) to learn more. +We welcome community contributions, check our [Contributing Guidelines](https://github.com/uxlfoundation/scikit-learn-intelex/blob/master/CONTRIBUTING.md) to learn more. ------------------------------------------------------------------------ \* The Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others. diff --git a/SECURITY.md b/SECURITY.md index 6a9f2c4146..febcfaf400 100644 --- a/SECURITY.md +++ b/SECURITY.md @@ -89,6 +89,6 @@ If you have any suggestions on how this Policy could be improved, submit an issue or a pull request to this repository. **Do not** report potential vulnerabilities or security flaws via a pull request. -[1]: https://github.com/intel/scikit-learn-intelex/releases/latest -[2]: https://github.com/intel/scikit-learn-intelex/security/advisories/new -[3]: https://github.com/intel/scikit-learn-intelex/security/advisories +[1]: https://github.com/uxlfoundation/scikit-learn-intelex/releases/latest +[2]: https://github.com/uxlfoundation/scikit-learn-intelex/security/advisories/new +[3]: https://github.com/uxlfoundation/scikit-learn-intelex/security/advisories diff --git a/SUPPORT.md b/SUPPORT.md index 740099713f..d8ddddb112 100644 --- a/SUPPORT.md +++ b/SUPPORT.md @@ -23,14 +23,14 @@ Use the following methods if you face any challenges. ## Issues -If you have a problem, check out the [GitHub Issues](https://github.com/intel/scikit-learn-intelex/issues) to see if the issue you want to address is already reported. +If you have a problem, check out the [GitHub Issues](https://github.com/uxlfoundation/scikit-learn-intelex/issues) to see if the issue you want to address is already reported. You may find users that have encountered the same bug or have similar ideas for changes or updates. You can use issues to report a problem, make a feature request, or add comments on an existing issue. ## Discussions -Visit the [GitHub Discussions](https://github.com/intel/scikit-learn-intelex/discussions) to engage with the community, ask questions, or help others. +Visit the [GitHub Discussions](https://github.com/uxlfoundation/scikit-learn-intelex/discussions) to engage with the community, ask questions, or help others. ## Forum diff --git a/conda-recipe/meta.yaml b/conda-recipe/meta.yaml index e8deda252c..f3dc30ffa3 100644 --- a/conda-recipe/meta.yaml +++ b/conda-recipe/meta.yaml @@ -28,7 +28,7 @@ package: # Reminder: source should point to path for repo or github archive for feedstock # source: -# url: https://github.com/intel/scikit-learn-intelex/archive/{{ version }}.tar.gz +# url: https://github.com/uxlfoundation/scikit-learn-intelex/archive/{{ version }}.tar.gz # sha256: ... source: path: .. @@ -99,7 +99,7 @@ test: - tests about: - home: https://intel.github.io/scikit-learn-intelex + home: https://uxlfoundation.github.io/scikit-learn-intelex license: Apache-2.0 license_file: - LICENSE @@ -114,8 +114,8 @@ about:

EULA: Apache-2.0

- dev_url: https://github.com/intel/scikit-learn-intelex - doc_url: https://intel.github.io/scikit-learn-intelex + dev_url: https://github.com/uxlfoundation/scikit-learn-intelex + doc_url: https://uxlfoundation.github.io/scikit-learn-intelex extra: recipe-maintainers: diff --git a/daal4py/README.md b/daal4py/README.md index a352e21011..8d7e288df1 100755 --- a/daal4py/README.md +++ b/daal4py/README.md @@ -23,15 +23,15 @@ We publish blogs on Medium, so [follow us](https://medium.com/intel-analytics-so ## šŸ”— Important links - [Documentation](https://intelpython.github.io/daal4py/) - [scikit-learn API and patching](https://intelpython.github.io/daal4py/sklearn.html#sklearn) -- [Building from Sources](https://github.com/intel/scikit-learn-intelex/blob/main/daal4py/INSTALL.md) -- [About Intel(R) oneAPI Data Analytics Library](https://github.com/oneapi-src/oneDAL) +- [Building from Sources](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/daal4py/INSTALL.md) +- [About Intel(R) oneAPI Data Analytics Library](https://github.com/uxlfoundation/oneDAL) ## šŸ’¬ Support Report issues, ask questions, and provide suggestions using: -- [GitHub Issues](https://github.com/intel/scikit-learn-intelex/issues) -- [GitHub Discussions](https://github.com/intel/scikit-learn-intelex/discussions) +- [GitHub Issues](https://github.com/uxlfoundation/scikit-learn-intelex/issues) +- [GitHub Discussions](https://github.com/uxlfoundation/scikit-learn-intelex/discussions) - [Forum](https://community.intel.com/t5/Intel-Distribution-for-Python/bd-p/distribution-python) You may reach out to project maintainers privately at onedal.maintainers@intel.com @@ -110,9 +110,9 @@ conda install impi_rt -c intel -You can [build daal4py from sources](https://github.com/intel/scikit-learn-intelex/blob/main/INSTALL.md) as well. +You can [build daal4py from sources](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/INSTALL.md) as well. # āš ļø Scikit-learn patching -Scikit-learn patching functionality in daal4py was deprecated and moved to a separate package - [Intel(R) Extension for Scikit-learn*](https://github.com/intel/scikit-learn-intelex). All future updates for the patching will be available in Intel(R) Extension for Scikit-learn only. Please use the package instead of daal4py for the Scikit-learn acceleration. +Scikit-learn patching functionality in daal4py was deprecated and moved to a separate package - [Intel(R) Extension for Scikit-learn*](https://github.com/uxlfoundation/scikit-learn-intelex). All future updates for the patching will be available in Intel(R) Extension for Scikit-learn only. Please use the package instead of daal4py for the Scikit-learn acceleration. diff --git a/deselected_tests.yaml b/deselected_tests.yaml index 8fc7eee3c0..57e36a9208 100755 --- a/deselected_tests.yaml +++ b/deselected_tests.yaml @@ -162,7 +162,7 @@ deselected_tests: - ensemble/tests/test_stacking.py::test_stacking_with_sample_weight[StackingClassifier] # Insufficient accuracy of "coefs" and "intercept" in Elastic Net for multi-target problems - # https://github.com/oneapi-src/oneDAL/issues/494 + # https://github.com/uxlfoundation/oneDAL/issues/494 - linear_model/tests/test_coordinate_descent.py::test_enet_multitarget # oneAPI Data Analytics Library (oneDAL) doesn't support sample_weight (back to scikit-learn), diff --git a/doc/README.md b/doc/README.md index fbbc927f32..1de5b43aff 100644 --- a/doc/README.md +++ b/doc/README.md @@ -25,7 +25,7 @@ To build Intel(R) Extension for Scikit-Learn documentation locally: 1. Clone the repository: - git clone https://github.com/intel/scikit-learn-intelex.git + git clone https://github.com/uxlfoundation/scikit-learn-intelex.git 2. Install required Python packages using `pip`: diff --git a/doc/daal4py/_templates/layout.html b/doc/daal4py/_templates/layout.html index 98cfe6e6f2..71d0d238e0 100644 --- a/doc/daal4py/_templates/layout.html +++ b/doc/daal4py/_templates/layout.html @@ -6,7 +6,7 @@ var wapLocalCode = 'us-en'; // Dynamically set per localized site, see mapping table for values var wapSection = "scikit-learn"; // WAP team will give you a unique section for your site // Load TMS - if(document.location.href.contains("intel.github.io/scikit-learn-intelex")){ + if(document.location.href.contains("uxlfoundation.github.io/scikit-learn-intelex")){ (function () { var url = 'https://www.intel.com/content/dam/www/global/wap/tms-loader.js'; // WAP file URL var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = url; diff --git a/doc/daal4py/algorithms.rst b/doc/daal4py/algorithms.rst index f0d8e7ef3c..3c2451d2ca 100755 --- a/doc/daal4py/algorithms.rst +++ b/doc/daal4py/algorithms.rst @@ -31,9 +31,9 @@ Parameters and semantics are described in |onedal-dg-classification-decision-for .. rubric:: Examples: - `Single-Process Decision Forest Classification Default Dense method - `__ + `__ - `Single-Process Decision Forest Classification Histogram method - `__ + `__ .. autoclass:: daal4py.decision_forest_classification_training :members: compute @@ -53,7 +53,7 @@ Parameters and semantics are described in |onedal-dg-classification-decision-tre .. rubric:: Examples: - `Single-Process Decision Tree Classification - `__ + `__ .. autoclass:: daal4py.decision_tree_classification_training :members: compute @@ -73,7 +73,7 @@ Parameters and semantics are described in |onedal-dg-classification-gradient-boo .. rubric:: Examples: - `Single-Process Gradient Boosted Classification - `__ + `__ .. autoclass:: daal4py.gbt_classification_training :members: compute @@ -93,7 +93,7 @@ Parameters and semantics are described in |onedal-dg-k-nearest-neighbors-knn|_. .. rubric:: Examples: - `Single-Process kNN - `__ + `__ .. autoclass:: daal4py.kdtree_knn_classification_training :members: compute @@ -128,7 +128,7 @@ Parameters and semantics are described in |onedal-dg-classification-adaboost|_. .. rubric:: Examples: - `Single-Process AdaBoost Classification - `__ + `__ .. autoclass:: daal4py.adaboost_training :members: compute @@ -148,7 +148,7 @@ Parameters and semantics are described in |onedal-dg-classification-brownboost|_ .. rubric:: Examples: - `Single-Process BrownBoost Classification - `__ + `__ .. autoclass:: daal4py.brownboost_training :members: compute @@ -168,7 +168,7 @@ Parameters and semantics are described in |onedal-dg-classification-logitboost|_ .. rubric:: Examples: - `Single-Process LogitBoost Classification - `__ + `__ .. autoclass:: daal4py.logitboost_training :members: compute @@ -188,7 +188,7 @@ Parameters and semantics are described in |onedal-dg-classification-weak-learner .. rubric:: Examples: - `Single-Process Stump Weak Learner Classification - `__ + `__ .. autoclass:: daal4py.stump_classification_training :members: compute @@ -207,9 +207,9 @@ Parameters and semantics are described in |onedal-dg-naive-bayes|_. .. rubric:: Examples: -- `Single-Process Naive Bayes `__ -- `Streaming Naive Bayes `__ -- `Multi-Process Naive Bayes `__ +- `Single-Process Naive Bayes `__ +- `Streaming Naive Bayes `__ +- `Multi-Process Naive Bayes `__ .. autoclass:: daal4py.multinomial_naive_bayes_training :members: compute @@ -231,7 +231,7 @@ Note: For the labels parameter, data is formatted as -1s and 1s .. rubric:: Examples: - `Single-Process SVM - `__ + `__ .. autoclass:: daal4py.svm_training :members: compute @@ -251,9 +251,9 @@ Parameters and semantics are described in |onedal-dg-logistic-regression|_. .. rubric:: Examples: - `Single-Process Binary Class Logistic Regression - `__ + `__ - `Single-Process Logistic Regression - `__ + `__ .. autoclass:: daal4py.logistic_regression_training :members: compute @@ -277,9 +277,9 @@ Parameters and semantics are described in |onedal-dg-regression-decision-forest| .. rubric:: Examples: - `Single-Process Decision Forest Regression Default Dense method - `__ + `__ - `Single-Process Decision Forest Regression Histogram method - `__ + `__ .. autoclass:: daal4py.decision_forest_regression_training :members: compute @@ -299,7 +299,7 @@ Parameters and semantics are described in |onedal-dg-regression-decision-tree|_. .. rubric:: Examples: - `Single-Process Decision Tree Regression - `__ + `__ .. autoclass:: daal4py.decision_tree_regression_training :members: compute @@ -319,7 +319,7 @@ Parameters and semantics are described in |onedal-dg-regression-gradient-boosted .. rubric:: Examples: - `Single-Process Boosted Regression Regression - `__ + `__ .. autoclass:: daal4py.gbt_regression_training :members: compute @@ -338,9 +338,9 @@ Parameters and semantics are described in |onedal-dg-linear-regression|_. .. rubric:: Examples: -- `Single-Process Linear Regression `__ -- `Streaming Linear Regression `__ -- `Multi-Process Linear Regression `__ +- `Single-Process Linear Regression `__ +- `Streaming Linear Regression `__ +- `Multi-Process Linear Regression `__ .. autoclass:: daal4py.linear_regression_training :members: compute @@ -359,7 +359,7 @@ Parameters and semantics are described in |onedal-dg-least-absolute-shrinkage-an .. rubric:: Examples: -- `Single-Process LASSO Regression `__ +- `Single-Process LASSO Regression `__ .. autoclass:: daal4py.lasso_regression_training :members: compute @@ -378,9 +378,9 @@ Parameters and semantics are described in |onedal-dg-ridge-regression|_. .. rubric:: Examples: -- `Single-Process Ridge Regression `__ -- `Streaming Ridge Regression `__ -- `Multi-Process Ridge Regression `__ +- `Single-Process Ridge Regression `__ +- `Streaming Ridge Regression `__ +- `Multi-Process Ridge Regression `__ .. autoclass:: daal4py.ridge_regression_training :members: compute @@ -400,7 +400,7 @@ Parameters and semantics are described in |onedal-dg-regression-stump|_. .. rubric:: Examples: - `Single-Process Stump Regression - `__ + `__ .. autoclass:: daal4py.stump_regression_training :members: compute @@ -419,8 +419,8 @@ Parameters and semantics are described in |onedal-dg-pca|_. .. rubric:: Examples: -- `Single-Process PCA `__ -- `Multi-Process PCA `__ +- `Single-Process PCA `__ +- `Multi-Process PCA `__ .. autoclass:: daal4py.pca :members: compute @@ -433,7 +433,7 @@ Parameters and semantics are described in |onedal-dg-pca-transform|_. .. rubric:: Examples: -- `Single-Process PCA Transform `__ +- `Single-Process PCA Transform `__ .. autoclass:: daal4py.pca_transform :members: compute @@ -446,8 +446,8 @@ Parameters and semantics are described in |onedal-dg-k-means-clustering|_. .. rubric:: Examples: -- `Single-Process K-Means `__ -- `Multi-Process K-Means `__ +- `Single-Process K-Means `__ +- `Multi-Process K-Means `__ K-Means Initialization ^^^^^^^^^^^^^^^^^^^^^^ @@ -473,7 +473,7 @@ Parameters and semantics are described in |onedal-dg-density-based-spatial-clust .. rubric:: Examples: -- `Single-Process DBSCAN `__ +- `Single-Process DBSCAN `__ .. autoclass:: daal4py.dbscan :members: compute @@ -488,7 +488,7 @@ Parameters and semantics are described in |onedal-dg-multivariate-outlier-detect .. rubric:: Examples: -- `Single-Process Multivariate Outlier Detection `__ +- `Single-Process Multivariate Outlier Detection `__ .. autoclass:: daal4py.multivariate_outlier_detection :members: compute @@ -501,7 +501,7 @@ Parameters and semantics are described in |onedal-dg-univariate-outlier-detectio .. rubric:: Examples: -- `Single-Process Univariate Outlier Detection `__ +- `Single-Process Univariate Outlier Detection `__ .. autoclass:: daal4py.univariate_outlier_detection :members: compute @@ -514,7 +514,7 @@ Parameters and semantics are described in |onedal-dg-multivariate-bacon-outlier- .. rubric:: Examples: -- `Single-Process Bacon Outlier Detection `__ +- `Single-Process Bacon Outlier Detection `__ .. autoclass:: daal4py.bacon_outlier_detection :members: compute @@ -530,9 +530,9 @@ Mean Squared Error Algorithm (MSE) Parameters and semantics are described in |onedal-dg-mse|_. .. rubric:: Examples: -- `In Adagrad `__ -- `In LBFGS `__ -- `In SGD `__ +- `In Adagrad `__ +- `In LBFGS `__ +- `In SGD `__ .. autoclass:: daal4py.optimization_solver_mse :members: compute, setup @@ -544,7 +544,7 @@ Logistic Loss Parameters and semantics are described in |onedal-dg-logistic-loss|_. .. rubric:: Examples: -- `In SGD `__ +- `In SGD `__ .. autoclass:: daal4py.optimization_solver_logistic_loss :members: compute, setup @@ -556,7 +556,7 @@ Cross-entropy Loss Parameters and semantics are described in |onedal-dg-cross-entropy-loss|_. .. rubric:: Examples: -- `In LBFGS `__ +- `In LBFGS `__ .. autoclass:: daal4py.optimization_solver_cross_entropy_loss :members: compute, setup @@ -570,8 +570,8 @@ Stochastic Gradient Descent Algorithm Parameters and semantics are described in |onedal-dg-sgd|_. .. rubric:: Examples: -- `Using Logistic Loss `__ -- `Using MSE `__ +- `Using Logistic Loss `__ +- `Using MSE `__ .. autoclass:: daal4py.optimization_solver_sgd :members: compute @@ -583,7 +583,7 @@ Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm Parameters and semantics are described in |onedal-dg-lbfgs|_. .. rubric:: Examples: -- `Using MSE `__ +- `Using MSE `__ .. autoclass:: daal4py.optimization_solver_lbfgs :members: compute @@ -595,7 +595,7 @@ Adaptive Subgradient Method Parameters and semantics are described in |onedal-dg-adagrad|_. .. rubric:: Examples: -- `Using MSE `__ +- `Using MSE `__ .. autoclass:: daal4py.optimization_solver_adagrad :members: compute @@ -607,7 +607,7 @@ Stochastic Average Gradient Descent Parameters and semantics are described in |onedal-dg-stochastic-average-gradient-descent-saga|_. .. rubric:: Examples: -- `Single Proces saga-logistc_loss `__ +- `Single Proces saga-logistc_loss `__ .. autoclass:: daal4py.optimization_solver_saga :members: compute @@ -622,7 +622,7 @@ Parameters and semantics are described in |onedal-dg-cosine-distance|_. .. rubric:: Examples: -- `Single-Process Cosine Distance `__ +- `Single-Process Cosine Distance `__ .. autoclass:: daal4py.cosine_distance :members: compute @@ -635,7 +635,7 @@ Parameters and semantics are described in |onedal-dg-correlation-distance|_. .. rubric:: Examples: -- `Single-Process Correlation Distance `__ +- `Single-Process Correlation Distance `__ .. autoclass:: daal4py.correlation_distance :members: compute @@ -652,7 +652,7 @@ Parameters and semantics are described in |onedal-dg-expectation-maximization-in .. rubric:: Examples: -- `Single-Process Expectation-Maximization `__ +- `Single-Process Expectation-Maximization `__ .. autoclass:: daal4py.em_gmm_init :members: compute @@ -665,7 +665,7 @@ Parameters and semantics are described in |onedal-dg-expectation-maximization-fo .. rubric:: Examples: -- `Single-Process Expectation-Maximization `__ +- `Single-Process Expectation-Maximization `__ .. autoclass:: daal4py.em_gmm :members: compute @@ -682,8 +682,8 @@ Parameters and semantics are described in |onedal-dg-qr-decomposition-without-pi .. rubric:: Examples: -- `Single-Process QR `__ -- `Streaming QR `__ +- `Single-Process QR `__ +- `Streaming QR `__ .. autoclass:: daal4py.qr :members: compute @@ -696,7 +696,7 @@ Parameters and semantics are described in |onedal-dg-pivoted-qr-decomposition|_. .. rubric:: Examples: -- `Single-Process Pivoted QR `__ +- `Single-Process Pivoted QR `__ .. autoclass:: daal4py.pivoted_qr :members: compute @@ -713,7 +713,7 @@ Parameters and semantics are described in |onedal-dg-z-score|_. .. rubric:: Examples: -- `Single-Process Z-Score Normalization `__ +- `Single-Process Z-Score Normalization `__ .. autoclass:: daal4py.normalization_zscore :members: compute @@ -726,7 +726,7 @@ Parameters and semantics are described in |onedal-dg-min-max|_. .. rubric:: Examples: -- `Single-Process Min-Max Normalization `__ +- `Single-Process Min-Max Normalization `__ .. autoclass:: daal4py.normalization_minmax :members: compute @@ -777,7 +777,7 @@ Parameters and semantics are described in |onedal-dg-bernoulli-distribution|_. .. rubric:: Examples: -- `Single-Process Bernoulli Distribution `__ +- `Single-Process Bernoulli Distribution `__ .. autoclass:: daal4py.distributions_bernoulli :members: compute @@ -790,7 +790,7 @@ Parameters and semantics are described in |onedal-dg-normal-distribution|_. .. rubric:: Examples: -- `Single-Process Normal Distribution `__ +- `Single-Process Normal Distribution `__ .. autoclass:: daal4py.distributions_normal :members: compute @@ -803,7 +803,7 @@ Parameters and semantics are described in |onedal-dg-uniform-distribution|_. .. rubric:: Examples: -- `Single-Process Uniform Distribution `__ +- `Single-Process Uniform Distribution `__ .. autoclass:: daal4py.distributions_uniform :members: compute @@ -816,7 +816,7 @@ Parameters and semantics are described in |onedal-dg-association-rules|_. .. rubric:: Examples: -- `Single-Process Association Rules `__ +- `Single-Process Association Rules `__ .. autoclass:: daal4py.association_rules :members: compute @@ -829,7 +829,7 @@ Parameters and semantics are described in |onedal-dg-cholesky-decomposition|_. .. rubric:: Examples: -- `Single-Process Cholesky `__ +- `Single-Process Cholesky `__ .. autoclass:: daal4py.cholesky :members: compute @@ -842,9 +842,9 @@ Parameters and semantics are described in |onedal-dg-correlation-and-variance-co .. rubric:: Examples: -- `Single-Process Covariance `__ -- `Streaming Covariance `__ -- `Multi-Process Covariance `__ +- `Single-Process Covariance `__ +- `Streaming Covariance `__ +- `Multi-Process Covariance `__ .. autoclass:: daal4py.covariance :members: compute @@ -857,7 +857,7 @@ Parameters and semantics are described in |onedal-dg-implicit-alternating-least- .. rubric:: Examples: -- `Single-Process implicit ALS `__ +- `Single-Process implicit ALS `__ .. autoclass:: daal4py.implicit_als_training :members: compute @@ -876,9 +876,9 @@ Parameters and semantics are described in |onedal-dg-moments-of-low-order|_. .. rubric:: Examples: -- `Single-Process Low Order Moments `__ -- `Streaming Low Order Moments `__ -- `Multi-Process Low Order Moments `__ +- `Single-Process Low Order Moments `__ +- `Streaming Low Order Moments `__ +- `Multi-Process Low Order Moments `__ .. autoclass:: daal4py.low_order_moments :members: compute @@ -891,7 +891,7 @@ Parameters and semantics are described in |onedal-dg-quantiles|_. .. rubric:: Examples: -- `Single-Process Quantiles `__ +- `Single-Process Quantiles `__ .. autoclass:: daal4py.quantiles :members: compute @@ -904,9 +904,9 @@ Parameters and semantics are described in |onedal-dg-svd|_. .. rubric:: Examples: -- `Single-Process SVD `__ -- `Streaming SVD `__ -- `Multi-Process SVD `__ +- `Single-Process SVD `__ +- `Streaming SVD `__ +- `Multi-Process SVD `__ .. autoclass:: daal4py.svd :members: compute @@ -919,7 +919,7 @@ Parameters and semantics are described in |onedal-dg-sorting|_. .. rubric:: Examples: -- `Single-Process Sorting `__ +- `Single-Process Sorting `__ .. autoclass:: daal4py.sorting :members: compute @@ -932,200 +932,200 @@ Trees .. rubric:: Examples: -- `Decision Forest Regression `__ -- `Decision Forest Classification `__ -- `Decision Tree Regression `__ -- `Decision Tree Classification `__ -- `Gradient Boosted Trees Regression `__ -- `Gradient Boosted Trees Classification `__ +- `Decision Forest Regression `__ +- `Decision Forest Classification `__ +- `Decision Tree Regression `__ +- `Decision Tree Classification `__ +- `Gradient Boosted Trees Regression `__ +- `Gradient Boosted Trees Classification `__ .. Link replacements .. |onedal-dg-bernoulli-distribution| replace:: Intel(R) oneAPI Data Analytics Library Bernoulli Distribution -.. _onedal-dg-bernoulli-distribution: https://oneapi-src.github.io/oneDAL/daal/algorithms/distributions/bernoulli.html +.. _onedal-dg-bernoulli-distribution: https://uxlfoundation.github.io/oneDAL/daal/algorithms/distributions/bernoulli.html .. |onedal-dg-svd| replace:: Intel(R) oneAPI Data Analytics Library SVD -.. _onedal-dg-svd: https://oneapi-src.github.io/oneDAL/daal/algorithms/svd/singular-value-decomposition.html +.. _onedal-dg-svd: https://uxlfoundation.github.io/oneDAL/daal/algorithms/svd/singular-value-decomposition.html .. |onedal-dg-regression| replace:: Intel(R) oneAPI Data Analytics Library Regression -.. _onedal-dg-regression: https://oneapi-src.github.io/oneDAL/daal/usage/training-and-prediction/regression.html +.. _onedal-dg-regression: https://uxlfoundation.github.io/oneDAL/daal/usage/training-and-prediction/regression.html .. |onedal-dg-k-means-clustering| replace:: Intel(R) oneAPI Data Analytics Library K-Means Clustering -.. _onedal-dg-k-means-clustering: https://oneapi-src.github.io/oneDAL/daal/algorithms/kmeans/k-means-clustering.html +.. _onedal-dg-k-means-clustering: https://uxlfoundation.github.io/oneDAL/daal/algorithms/kmeans/k-means-clustering.html .. |onedal-dg-lbfgs| replace:: Intel(R) oneAPI Data Analytics Library LBFGS -.. _onedal-dg-lbfgs: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/limited-memory-broyden-fletcher-goldfarb-shanno-algorithm.html +.. _onedal-dg-lbfgs: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/limited-memory-broyden-fletcher-goldfarb-shanno-algorithm.html .. |onedal-dg-naive-bayes| replace:: Intel(R) oneAPI Data Analytics Library Naive Bayes -.. _onedal-dg-naive-bayes: https://oneapi-src.github.io/oneDAL/daal/algorithms/naive_bayes/naive-bayes-classifier.html +.. _onedal-dg-naive-bayes: https://uxlfoundation.github.io/oneDAL/daal/algorithms/naive_bayes/naive-bayes-classifier.html .. |onedal-dg-expectation-maximization| replace:: Intel(R) oneAPI Data Analytics Library Expectation-Maximization -.. _onedal-dg-expectation-maximization: https://oneapi-src.github.io/oneDAL/daal/algorithms/em/expectation-maximization.html +.. _onedal-dg-expectation-maximization: https://uxlfoundation.github.io/oneDAL/daal/algorithms/em/expectation-maximization.html .. |onedal-dg-mcg59| replace:: Intel(R) oneAPI Data Analytics Library mcg59 -.. _onedal-dg-mcg59: https://oneapi-src.github.io/oneDAL/daal/algorithms/engines/mcg59.html +.. _onedal-dg-mcg59: https://uxlfoundation.github.io/oneDAL/daal/algorithms/engines/mcg59.html .. |onedal-dg-least-absolute-shrinkage-and-selection-operator| replace:: Intel(R) oneAPI Data Analytics Library Least Absolute Shrinkage and Selection Operator -.. _onedal-dg-least-absolute-shrinkage-and-selection-operator: https://oneapi-src.github.io/oneDAL/daal/algorithms/lasso_elastic_net/lasso.html +.. _onedal-dg-least-absolute-shrinkage-and-selection-operator: https://uxlfoundation.github.io/oneDAL/daal/algorithms/lasso_elastic_net/lasso.html .. |onedal-dg-sorting| replace:: Intel(R) oneAPI Data Analytics Library Sorting -.. _onedal-dg-sorting: https://oneapi-src.github.io/oneDAL/daal/algorithms/sorting/index.html +.. _onedal-dg-sorting: https://uxlfoundation.github.io/oneDAL/daal/algorithms/sorting/index.html .. |onedal-dg-expectation-maximization-for-the-gaussian-mixture-model| replace:: Intel(R) oneAPI Data Analytics Library Expectation-Maximization for the Gaussian Mixture Model -.. _onedal-dg-expectation-maximization-for-the-gaussian-mixture-model: https://oneapi-src.github.io/oneDAL/daal/algorithms/em/expectation-maximization.html#em-algorithm-for-the-gaussian-mixture-model +.. _onedal-dg-expectation-maximization-for-the-gaussian-mixture-model: https://uxlfoundation.github.io/oneDAL/daal/algorithms/em/expectation-maximization.html#em-algorithm-for-the-gaussian-mixture-model .. |onedal-dg-multivariate-outlier-detection| replace:: Intel(R) oneAPI Data Analytics Library Multivariate Outlier Detection -.. _onedal-dg-multivariate-outlier-detection: https://oneapi-src.github.io/oneDAL/daal/algorithms/outlier_detection/multivariate.html +.. _onedal-dg-multivariate-outlier-detection: https://uxlfoundation.github.io/oneDAL/daal/algorithms/outlier_detection/multivariate.html .. |onedal-dg-expectation-maximization-initialization| replace:: Intel(R) oneAPI Data Analytics Library Expectation-Maximization Initialization -.. _onedal-dg-expectation-maximization-initialization: https://oneapi-src.github.io/oneDAL/daal/algorithms/em/expectation-maximization.html#initialization +.. _onedal-dg-expectation-maximization-initialization: https://uxlfoundation.github.io/oneDAL/daal/algorithms/em/expectation-maximization.html#initialization .. |onedal-dg-pivoted-qr-decomposition| replace:: Intel(R) oneAPI Data Analytics Library Pivoted QR Decomposition -.. _onedal-dg-pivoted-qr-decomposition: https://oneapi-src.github.io/oneDAL/daal/algorithms/qr/qr-pivoted.html +.. _onedal-dg-pivoted-qr-decomposition: https://uxlfoundation.github.io/oneDAL/daal/algorithms/qr/qr-pivoted.html .. |onedal-dg-regression-decision-tree| replace:: Intel(R) oneAPI Data Analytics Library Regression Decision Tree -.. _onedal-dg-regression-decision-tree: https://oneapi-src.github.io/oneDAL/daal/algorithms/decision_tree/decision-tree-regression.html +.. _onedal-dg-regression-decision-tree: https://uxlfoundation.github.io/oneDAL/daal/algorithms/decision_tree/decision-tree-regression.html .. |onedal-dg-k-nearest-neighbors-knn| replace:: Intel(R) oneAPI Data Analytics Library k-Nearest Neighbors (kNN) -.. _onedal-dg-k-nearest-neighbors-knn: https://oneapi-src.github.io/oneDAL/daal/algorithms/k_nearest_neighbors/k-nearest-neighbors-knn-classifier.html +.. _onedal-dg-k-nearest-neighbors-knn: https://uxlfoundation.github.io/oneDAL/daal/algorithms/k_nearest_neighbors/k-nearest-neighbors-knn-classifier.html .. |onedal-dg-pca| replace:: Intel(R) oneAPI Data Analytics Library PCA -.. _onedal-dg-pca: https://oneapi-src.github.io/oneDAL/daal/algorithms/pca/principal-component-analysis.html +.. _onedal-dg-pca: https://uxlfoundation.github.io/oneDAL/daal/algorithms/pca/principal-component-analysis.html .. |onedal-dg-sgd| replace:: Intel(R) oneAPI Data Analytics Library SGD -.. _onedal-dg-sgd: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/stochastic-gradient-descent-algorithm.html +.. _onedal-dg-sgd: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/stochastic-gradient-descent-algorithm.html .. |onedal-dg-uniform-distribution| replace:: Intel(R) oneAPI Data Analytics Library Uniform Distribution -.. _onedal-dg-uniform-distribution: https://oneapi-src.github.io/oneDAL/daal/algorithms/distributions/uniform.html +.. _onedal-dg-uniform-distribution: https://uxlfoundation.github.io/oneDAL/daal/algorithms/distributions/uniform.html .. |onedal-dg-cross-entropy-loss| replace:: Intel(R) oneAPI Data Analytics Library Cross Entropy Loss -.. _onedal-dg-cross-entropy-loss: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/objective-functions/cross-entropy.html +.. _onedal-dg-cross-entropy-loss: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/objective-functions/cross-entropy.html .. |onedal-dg-classification| replace:: Intel(R) oneAPI Data Analytics Library Classification -.. _onedal-dg-classification: https://oneapi-src.github.io/oneDAL/daal/usage/training-and-prediction/classification.html +.. _onedal-dg-classification: https://uxlfoundation.github.io/oneDAL/daal/usage/training-and-prediction/classification.html .. |onedal-dg-cosine-distance| replace:: Intel(R) oneAPI Data Analytics Library Cosine Distance -.. _onedal-dg-cosine-distance: https://oneapi-src.github.io/oneDAL/daal/algorithms/distance/cosine.html +.. _onedal-dg-cosine-distance: https://uxlfoundation.github.io/oneDAL/daal/algorithms/distance/cosine.html .. |onedal-dg-regression-stump| replace:: Intel(R) oneAPI Data Analytics Library Regression Stump -.. _onedal-dg-regression-stump: https://oneapi-src.github.io/oneDAL/daal/algorithms/stump/regression.html +.. _onedal-dg-regression-stump: https://uxlfoundation.github.io/oneDAL/daal/algorithms/stump/regression.html .. |onedal-dg-multivariate-bacon-outlier-detection| replace:: Intel(R) oneAPI Data Analytics Library Multivariate Bacon Outlier Detection -.. _onedal-dg-multivariate-bacon-outlier-detection: https://oneapi-src.github.io/oneDAL/daal/algorithms/outlier_detection/multivariate-bacon.html +.. _onedal-dg-multivariate-bacon-outlier-detection: https://uxlfoundation.github.io/oneDAL/daal/algorithms/outlier_detection/multivariate-bacon.html .. |onedal-dg-logistic-regression| replace:: Intel(R) oneAPI Data Analytics Library Logistic Regression -.. _onedal-dg-logistic-regression: https://oneapi-src.github.io/oneDAL/daal/algorithms/logistic_regression/logistic-regression.html +.. _onedal-dg-logistic-regression: https://uxlfoundation.github.io/oneDAL/daal/algorithms/logistic_regression/logistic-regression.html .. |onedal-dg-quantiles| replace:: Intel(R) oneAPI Data Analytics Library Quantiles -.. _onedal-dg-quantiles: https://oneapi-src.github.io/oneDAL/daal/algorithms/quantiles/index.html +.. _onedal-dg-quantiles: https://uxlfoundation.github.io/oneDAL/daal/algorithms/quantiles/index.html .. |onedal-dg-pca-transform| replace:: Intel(R) oneAPI Data Analytics Library PCA Transform -.. _onedal-dg-pca-transform: https://oneapi-src.github.io/oneDAL/daal/algorithms/pca/transform.html +.. _onedal-dg-pca-transform: https://uxlfoundation.github.io/oneDAL/daal/algorithms/pca/transform.html .. |onedal-dg-correlation-distance| replace:: Intel(R) oneAPI Data Analytics Library Correlation Distance -.. _onedal-dg-correlation-distance: https://oneapi-src.github.io/oneDAL/daal/algorithms/distance/correlation.html +.. _onedal-dg-correlation-distance: https://uxlfoundation.github.io/oneDAL/daal/algorithms/distance/correlation.html .. |onedal-dg-association-rules| replace:: Intel(R) oneAPI Data Analytics Library Association Rules -.. _onedal-dg-association-rules: https://oneapi-src.github.io/oneDAL/daal/algorithms/association_rules/association-rules.html +.. _onedal-dg-association-rules: https://uxlfoundation.github.io/oneDAL/daal/algorithms/association_rules/association-rules.html .. |onedal-dg-univariate-outlier-detection| replace:: Intel(R) oneAPI Data Analytics Library Univariate Outlier Detection -.. _onedal-dg-univariate-outlier-detection: https://oneapi-src.github.io/oneDAL/daal/algorithms/outlier_detection/univariate.html +.. _onedal-dg-univariate-outlier-detection: https://uxlfoundation.github.io/oneDAL/daal/algorithms/outlier_detection/univariate.html .. |onedal-dg-classification-gradient-boosted-tree| replace:: Intel(R) oneAPI Data Analytics Library Classification Gradient Boosted Tree -.. _onedal-dg-classification-gradient-boosted-tree: https://oneapi-src.github.io/oneDAL/daal/algorithms/gradient_boosted_trees/gradient-boosted-trees-classification.html +.. _onedal-dg-classification-gradient-boosted-tree: https://uxlfoundation.github.io/oneDAL/daal/algorithms/gradient_boosted_trees/gradient-boosted-trees-classification.html .. |onedal-dg-classification-brownboost| replace:: Intel(R) oneAPI Data Analytics Library Classification BrownBoost -.. _onedal-dg-classification-brownboost: https://oneapi-src.github.io/oneDAL/daal/algorithms/boosting/brownboost.html +.. _onedal-dg-classification-brownboost: https://uxlfoundation.github.io/oneDAL/daal/algorithms/boosting/brownboost.html .. |onedal-dg-regression-decision-forest| replace:: Intel(R) oneAPI Data Analytics Library Regression Decision Forest -.. _onedal-dg-regression-decision-forest: https://oneapi-src.github.io/oneDAL/daal/algorithms/decision_forest/decision-forest-regression.html +.. _onedal-dg-regression-decision-forest: https://uxlfoundation.github.io/oneDAL/daal/algorithms/decision_forest/decision-forest-regression.html .. |onedal-dg-z-score| replace:: Intel(R) oneAPI Data Analytics Library Z-Score -.. _onedal-dg-z-score: https://oneapi-src.github.io/oneDAL/daal/algorithms/normalization/z-score.html +.. _onedal-dg-z-score: https://uxlfoundation.github.io/oneDAL/daal/algorithms/normalization/z-score.html .. |onedal-dg-classification-weak-learner-stump| replace:: Intel(R) oneAPI Data Analytics Library Classification Weak Learner Stump -.. _onedal-dg-classification-weak-learner-stump: https://oneapi-src.github.io/oneDAL/daal/algorithms/stump/classification.html +.. _onedal-dg-classification-weak-learner-stump: https://uxlfoundation.github.io/oneDAL/daal/algorithms/stump/classification.html .. |onedal-dg-svm| replace:: Intel(R) oneAPI Data Analytics Library SVM -.. _onedal-dg-svm: https://oneapi-src.github.io/oneDAL/daal/algorithms/svm/support-vector-machine-classifier.html +.. _onedal-dg-svm: https://uxlfoundation.github.io/oneDAL/daal/algorithms/svm/support-vector-machine-classifier.html .. |onedal-dg-regression-gradient-boosted-tree| replace:: Intel(R) oneAPI Data Analytics Library Regression Gradient Boosted Tree -.. _onedal-dg-regression-gradient-boosted-tree: https://oneapi-src.github.io/oneDAL/daal/algorithms/gradient_boosted_trees/gradient-boosted-trees-regression.html +.. _onedal-dg-regression-gradient-boosted-tree: https://uxlfoundation.github.io/oneDAL/daal/algorithms/gradient_boosted_trees/gradient-boosted-trees-regression.html .. |onedal-dg-logistic-loss| replace:: Intel(R) oneAPI Data Analytics Library Logistic Loss -.. _onedal-dg-logistic-loss: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/objective-functions/logistic-loss.html +.. _onedal-dg-logistic-loss: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/objective-functions/logistic-loss.html .. |onedal-dg-adagrad| replace:: Intel(R) oneAPI Data Analytics Library AdaGrad -.. _onedal-dg-adagrad: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/adaptive-subgradient-method.html +.. _onedal-dg-adagrad: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/adaptive-subgradient-method.html .. |onedal-dg-qr-decomposition| replace:: Intel(R) oneAPI Data Analytics Library QR Decomposition -.. _onedal-dg-qr-decomposition: https://oneapi-src.github.io/oneDAL/daal/algorithms/qr/qr-decomposition.html +.. _onedal-dg-qr-decomposition: https://uxlfoundation.github.io/oneDAL/daal/algorithms/qr/qr-decomposition.html .. |onedal-dg-mt19937| replace:: Intel(R) oneAPI Data Analytics Library mt19937 -.. _onedal-dg-mt19937: https://oneapi-src.github.io/oneDAL/daal/algorithms/engines/mt19937.html +.. _onedal-dg-mt19937: https://uxlfoundation.github.io/oneDAL/daal/algorithms/engines/mt19937.html .. |onedal-dg-implicit-alternating-least-squares| replace:: Intel(R) oneAPI Data Analytics Library Implicit Alternating Least Squares -.. _onedal-dg-implicit-alternating-least-squares: https://oneapi-src.github.io/oneDAL/daal/algorithms/implicit_als/implicit-alternating-least-squares.html +.. _onedal-dg-implicit-alternating-least-squares: https://uxlfoundation.github.io/oneDAL/daal/algorithms/implicit_als/implicit-alternating-least-squares.html .. |onedal-dg-linear-regression| replace:: Intel(R) oneAPI Data Analytics Library Linear Regression -.. _onedal-dg-linear-regression: https://oneapi-src.github.io/oneDAL/daal/algorithms/linear_ridge_regression/linear-regression.html +.. _onedal-dg-linear-regression: https://uxlfoundation.github.io/oneDAL/daal/algorithms/linear_ridge_regression/linear-regression.html .. |onedal-dg-classification-adaboost| replace:: Intel(R) oneAPI Data Analytics Library Classification AdaBoost -.. _onedal-dg-classification-adaboost: https://oneapi-src.github.io/oneDAL/daal/algorithms/boosting/adaboost.html +.. _onedal-dg-classification-adaboost: https://uxlfoundation.github.io/oneDAL/daal/algorithms/boosting/adaboost.html .. |onedal-dg-distributions| replace:: Intel(R) oneAPI Data Analytics Library Distributions -.. _onedal-dg-distributions: https://oneapi-src.github.io/oneDAL/daal/algorithms/distributions/index.html +.. _onedal-dg-distributions: https://uxlfoundation.github.io/oneDAL/daal/algorithms/distributions/index.html .. |onedal-dg-correlation-and-variance-covariance-matrices| replace:: Intel(R) oneAPI Data Analytics Library Correlation and Variance-Covariance Matrices -.. _onedal-dg-correlation-and-variance-covariance-matrices: https://oneapi-src.github.io/oneDAL/daal/algorithms/covariance/correlation-and-variance-covariance-matrices.html +.. _onedal-dg-correlation-and-variance-covariance-matrices: https://uxlfoundation.github.io/oneDAL/daal/algorithms/covariance/correlation-and-variance-covariance-matrices.html .. |onedal-dg-classification-decision-tree| replace:: Intel(R) oneAPI Data Analytics Library Classification Decision Tree -.. _onedal-dg-classification-decision-tree: https://oneapi-src.github.io/oneDAL/daal/algorithms/decision_tree/decision-tree-classification.html +.. _onedal-dg-classification-decision-tree: https://uxlfoundation.github.io/oneDAL/daal/algorithms/decision_tree/decision-tree-classification.html .. |onedal-dg-ridge-regression| replace:: Intel(R) oneAPI Data Analytics Library Ridge Regression -.. _onedal-dg-ridge-regression: https://oneapi-src.github.io/oneDAL/daal/algorithms/linear_ridge_regression/ridge-regression.html +.. _onedal-dg-ridge-regression: https://uxlfoundation.github.io/oneDAL/daal/algorithms/linear_ridge_regression/ridge-regression.html .. |onedal-dg-classification-logitboost| replace:: Intel(R) oneAPI Data Analytics Library Classification LogitBoost -.. _onedal-dg-classification-logitboost: https://oneapi-src.github.io/oneDAL/daal/algorithms/boosting/logitboost.html +.. _onedal-dg-classification-logitboost: https://uxlfoundation.github.io/oneDAL/daal/algorithms/boosting/logitboost.html .. |onedal-dg-k-means-initialization| replace:: Intel(R) oneAPI Data Analytics Library K-Means Initialization -.. _onedal-dg-k-means-initialization: https://oneapi-src.github.io/oneDAL/daal/algorithms/kmeans/k-means-clustering.html#initialization +.. _onedal-dg-k-means-initialization: https://uxlfoundation.github.io/oneDAL/daal/algorithms/kmeans/k-means-clustering.html#initialization .. |onedal-dg-qr-decomposition-without-pivoting| replace:: Intel(R) oneAPI Data Analytics Library QR Decomposition without pivoting -.. _onedal-dg-qr-decomposition-without-pivoting: https://oneapi-src.github.io/oneDAL/daal/algorithms/qr/qr-without-pivoting.html +.. _onedal-dg-qr-decomposition-without-pivoting: https://uxlfoundation.github.io/oneDAL/daal/algorithms/qr/qr-without-pivoting.html .. |onedal-dg-mse| replace:: Intel(R) oneAPI Data Analytics Library MSE -.. _onedal-dg-mse: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/objective-functions/mse.html +.. _onedal-dg-mse: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/objective-functions/mse.html .. |onedal-dg-stochastic-average-gradient-descent-saga| replace:: Intel(R) oneAPI Data Analytics Library Stochastic Average Gradient Descent SAGA -.. _onedal-dg-stochastic-average-gradient-descent-saga: https://oneapi-src.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/stochastic-average-gradient-accelerated-method.html +.. _onedal-dg-stochastic-average-gradient-descent-saga: https://uxlfoundation.github.io/oneDAL/daal/algorithms/optimization-solvers/solvers/stochastic-average-gradient-accelerated-method.html .. |onedal-dg-engines| replace:: Intel(R) oneAPI Data Analytics Library Engines -.. _onedal-dg-engines: https://oneapi-src.github.io/oneDAL/daal/algorithms/engines/index.html +.. _onedal-dg-engines: https://uxlfoundation.github.io/oneDAL/daal/algorithms/engines/index.html .. |onedal-dg-cholesky-decomposition| replace:: Intel(R) oneAPI Data Analytics Library Cholesky Decomposition -.. _onedal-dg-cholesky-decomposition: https://oneapi-src.github.io/oneDAL/daal/algorithms/cholesky/cholesky.html +.. _onedal-dg-cholesky-decomposition: https://uxlfoundation.github.io/oneDAL/daal/algorithms/cholesky/cholesky.html .. |onedal-dg-classification-decision-forest| replace:: Intel(R) oneAPI Data Analytics Library Classification Decision Forest -.. _onedal-dg-classification-decision-forest: https://oneapi-src.github.io/oneDAL/daal/algorithms/decision_forest/decision-forest-classification.html +.. _onedal-dg-classification-decision-forest: https://uxlfoundation.github.io/oneDAL/daal/algorithms/decision_forest/decision-forest-classification.html .. |onedal-dg-normalization| replace:: Intel(R) oneAPI Data Analytics Library Normalization -.. _onedal-dg-normalization: https://oneapi-src.github.io/oneDAL/daal/algorithms/normalization/index.html +.. _onedal-dg-normalization: https://uxlfoundation.github.io/oneDAL/daal/algorithms/normalization/index.html .. |onedal-dg-density-based-spatial-clustering-of-applications-with-noise| replace:: Intel(R) oneAPI Data Analytics Library Density-Based Spatial Clustering of Applications with Noise -.. _onedal-dg-density-based-spatial-clustering-of-applications-with-noise: https://oneapi-src.github.io/oneDAL/daal/algorithms/dbscan/index.html +.. _onedal-dg-density-based-spatial-clustering-of-applications-with-noise: https://uxlfoundation.github.io/oneDAL/daal/algorithms/dbscan/index.html .. |onedal-dg-moments-of-low-order| replace:: Intel(R) oneAPI Data Analytics Library Moments of Low Order -.. _onedal-dg-moments-of-low-order: https://oneapi-src.github.io/oneDAL/daal/algorithms/moments/moments-of-low-order.html +.. _onedal-dg-moments-of-low-order: https://uxlfoundation.github.io/oneDAL/daal/algorithms/moments/moments-of-low-order.html .. |onedal-dg-mt2203| replace:: Intel(R) oneAPI Data Analytics Library mt2203 -.. _onedal-dg-mt2203: https://oneapi-src.github.io/oneDAL/daal/algorithms/engines/mt2203.html +.. _onedal-dg-mt2203: https://uxlfoundation.github.io/oneDAL/daal/algorithms/engines/mt2203.html .. |onedal-dg-normal-distribution| replace:: Intel(R) oneAPI Data Analytics Library Normal Distribution -.. _onedal-dg-normal-distribution: https://oneapi-src.github.io/oneDAL/daal/algorithms/distributions/normal.html +.. _onedal-dg-normal-distribution: https://uxlfoundation.github.io/oneDAL/daal/algorithms/distributions/normal.html .. |onedal-dg-k-means-computation| replace:: Intel(R) oneAPI Data Analytics Library K-Means Computation -.. _onedal-dg-k-means-computation: https://oneapi-src.github.io/oneDAL/daal/algorithms/kmeans/k-means-clustering.html#computation +.. _onedal-dg-k-means-computation: https://uxlfoundation.github.io/oneDAL/daal/algorithms/kmeans/k-means-clustering.html#computation .. |onedal-dg-min-max| replace:: Intel(R) oneAPI Data Analytics Library Min-Max -.. _onedal-dg-min-max: https://oneapi-src.github.io/oneDAL/daal/algorithms/normalization/min-max.html +.. _onedal-dg-min-max: https://uxlfoundation.github.io/oneDAL/daal/algorithms/normalization/min-max.html diff --git a/doc/daal4py/examples.rst b/doc/daal4py/examples.rst index 181b2c50ab..a4be55d9b4 100755 --- a/doc/daal4py/examples.rst +++ b/doc/daal4py/examples.rst @@ -27,155 +27,155 @@ General usage Building models from Gradient Boosting frameworks -- `XGBoost* model conversion `_ -- `LightGBM* model conversion `_ -- `CatBoost* model conversion `_ +- `XGBoost* model conversion `_ +- `LightGBM* model conversion `_ +- `CatBoost* model conversion `_ Principal Component Analysis (PCA) Transform -- `Single-Process PCA `_ -- `Multi-Process PCA `_ +- `Single-Process PCA `_ +- `Multi-Process PCA `_ Singular Value Decomposition (SVD) -- `Single-Process PCA Transform `_ +- `Single-Process PCA Transform `_ -- `Single-Process SVD `_ -- `Streaming SVD `_ -- `Multi-Process SVD `_ +- `Single-Process SVD `_ +- `Streaming SVD `_ +- `Multi-Process SVD `_ Moments of Low Order -- `Single-Process Low Order Moments `_ -- `Streaming Low Order Moments `_ -- `Multi-Process Low Order Moments `_ +- `Single-Process Low Order Moments `_ +- `Streaming Low Order Moments `_ +- `Multi-Process Low Order Moments `_ Correlation and Variance-Covariance Matrices -- `Single-Process Covariance `_ -- `Streaming Covariance `_ -- `Multi-Process Covariance `_ +- `Single-Process Covariance `_ +- `Streaming Covariance `_ +- `Multi-Process Covariance `_ Decision Forest Classification - `Single-Process Decision Forest Classification Default Dense method - `_ + `_ - `Single-Process Decision Forest Classification Histogram method - `_ + `_ Decision Tree Classification - `Single-Process Decision Tree Classification - `_ + `_ Gradient Boosted Classification - `Single-Process Gradient Boosted Classification - `_ + `_ k-Nearest Neighbors (kNN) - `Single-Process kNN - `_ + `_ Multinomial Naive Bayes -- `Single-Process Naive Bayes `_ -- `Streaming Naive Bayes `_ -- `Multi-Process Naive Bayes `_ +- `Single-Process Naive Bayes `_ +- `Streaming Naive Bayes `_ +- `Multi-Process Naive Bayes `_ Support Vector Machine (SVM) - `Single-Process Binary SVM - `_ + `_ - `Single-Process Muticlass SVM - `_ + `_ Logistic Regression - `Single-Process Binary Class Logistic Regression - `_ + `_ - `Single-Process Logistic Regression - `_ + `_ Decision Forest Regression - `Single-Process Decision Forest Regression Default Dense method - `_ + `_ - `Single-Process Decision Forest Regression Histogram method - `_ + `_ - `Single-Process Decision Tree Regression - `_ + `_ Gradient Boosted Regression - `Single-Process Boosted Regression - `_ + `_ Linear Regression -- `Single-Process Linear Regression `_ -- `Streaming Linear Regression `_ -- `Multi-Process Linear Regression `_ +- `Single-Process Linear Regression `_ +- `Streaming Linear Regression `_ +- `Multi-Process Linear Regression `_ Ridge Regression -- `Single-Process Ridge Regression `_ -- `Streaming Ridge Regression `_ -- `Multi-Process Ridge Regression `_ +- `Single-Process Ridge Regression `_ +- `Streaming Ridge Regression `_ +- `Multi-Process Ridge Regression `_ K-Means Clustering -- `Single-Process K-Means `_ -- `Multi-Process K-Means `_ +- `Single-Process K-Means `_ +- `Multi-Process K-Means `_ Multivariate Outlier Detection -- `Single-Process Multivariate Outlier Detection `_ +- `Single-Process Multivariate Outlier Detection `_ Univariate Outlier Detection -- `Single-Process Univariate Outlier Detection `_ +- `Single-Process Univariate Outlier Detection `_ Optimization Solvers-Mean Squared Error Algorithm (MSE) -- `MSE In Adagrad `_ -- `MSE In LBFGS `_ -- `MSE In SGD `_ +- `MSE In Adagrad `_ +- `MSE In LBFGS `_ +- `MSE In SGD `_ Logistic Loss -- `Logistic Loss SGD `_ +- `Logistic Loss SGD `_ Stochastic Gradient Descent Algorithm -- `Stochastic Gradient Descent Algorithm Using Logistic Loss `_ -- `Stochastic Gradient Descent Algorithm Using MSE `_ +- `Stochastic Gradient Descent Algorithm Using Logistic Loss `_ +- `Stochastic Gradient Descent Algorithm Using MSE `_ Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm -- `Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm - Using MSE `_ +- `Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm - Using MSE `_ Adaptive Subgradient Method -- `Adaptive Subgradient Method Using MSE `_ +- `Adaptive Subgradient Method Using MSE `_ Cosine Distance Matrix -- `Single-Process Cosine Distance `_ +- `Single-Process Cosine Distance `_ Correlation Distance Matrix -- `Single-Process Correlation Distance `_ +- `Single-Process Correlation Distance `_ Trees -- `Decision Forest Regression `_ -- `Decision Forest Classification `_ -- `Decision Tree Regression `_ -- `Decision Tree Classification `_ -- `Gradient Boosted Trees Regression `_ -- `Gradient Boosted Trees Classification `_ +- `Decision Forest Regression `_ +- `Decision Forest Classification `_ +- `Decision Tree Regression `_ +- `Decision Tree Classification `_ +- `Gradient Boosted Trees Regression `_ +- `Gradient Boosted Trees Classification `_ diff --git a/doc/daal4py/index.rst b/doc/daal4py/index.rst index f558717133..4af3d38aea 100644 --- a/doc/daal4py/index.rst +++ b/doc/daal4py/index.rst @@ -102,7 +102,7 @@ Last but not least, daal4py allows :ref:`getting input data from streams `_ +daal4py oneAPI and GPU support is deprecated. Use `scikit-learn-intelex `_ instead. @@ -146,11 +146,11 @@ daal4py is available at the `Python Package Index `_ and in `Intel channel `_. Sources and build instructions are available in -`daal4py repository `_. +`daal4py repository `_. The daal4py package is available via same distribution channels and platforms as scikit-learn-intelex. See -`scikit-learn-intelex requirements ` _ +`scikit-learn-intelex requirements ` _ - Install from PyPI:: @@ -194,7 +194,7 @@ Scikit-Learn API and patching ----------------------------- .. tip:: We recommend using - the 'scikit-learn-intelex package patching ' _ for the scikit-learn patching. + the 'scikit-learn-intelex package patching ' _ for the scikit-learn patching. daal4py exposes some oneDAL solvers using a scikit-learn compatible API. daal4py can furthermore monkey-patch the ``sklearn`` package to use the DAAL diff --git a/doc/daal4py/model-builders.rst b/doc/daal4py/model-builders.rst index 55dc292ef4..86e4ca7182 100644 --- a/doc/daal4py/model-builders.rst +++ b/doc/daal4py/model-builders.rst @@ -130,10 +130,10 @@ Examples --------------------------------- Model Builders models conversion -- `XGBoost model conversion `_ -- `SHAP value prediction from an XGBoost model `_ -- `LightGBM model conversion `_ -- `CatBoost model conversion `_ +- `XGBoost model conversion `_ +- `SHAP value prediction from an XGBoost model `_ +- `LightGBM model conversion `_ +- `CatBoost model conversion `_ Articles and Blog Posts --------------------------------- diff --git a/doc/daal4py/note.rst b/doc/daal4py/note.rst index f22445eb1c..c7fe1b09e3 100644 --- a/doc/daal4py/note.rst +++ b/doc/daal4py/note.rst @@ -16,5 +16,5 @@ .. _note: -.. note:: Scikit-learn patching functionality in daal4py was deprecated and moved to a separate package, `Intel(R) Extension for Scikit-learn* `_. +.. note:: Scikit-learn patching functionality in daal4py was deprecated and moved to a separate package, `Intel(R) Extension for Scikit-learn* `_. All future patches will be available only in Intel(R) Extension for Scikit-learn*. Use the scikit-learn-intelex package instead of daal4py for the scikit-learn acceleration. diff --git a/doc/daal4py/scaling.rst b/doc/daal4py/scaling.rst index 824b8c815a..ba21cb5c85 100644 --- a/doc/daal4py/scaling.rst +++ b/doc/daal4py/scaling.rst @@ -76,36 +76,36 @@ The following algorithms support distribution: - PCA (pca) - - `PCA `_ + - `PCA `_ - SVD (svd) - - `SVD `_ + - `SVD `_ - Linear Regression Training (linear_regression_training) - - `Linear Regression `_ + - `Linear Regression `_ - Ridge Regression Training (ridge_regression_training) - - `Ridge Regression `_ + - `Ridge Regression `_ - Multinomial Naive Bayes Training (multinomial_naive_bayes_training) - - `Naive Bayes `_ + - `Naive Bayes `_ - K-Means (kmeans_init and kmeans) - - `K-Means `_ + - `K-Means `_ - Correlation and Variance-Covariance Matrices (covariance) - - `Covariance `_ + - `Covariance `_ - Moments of Low Order (low_order_moments) - - `Low Order Moments `_ + - `Low Order Moments `_ - QR Decomposition (qr) - - `QR `_ + - `QR `_ diff --git a/doc/daal4py/sklearn.rst b/doc/daal4py/sklearn.rst index 2693889b84..478885bae9 100755 --- a/doc/daal4py/sklearn.rst +++ b/doc/daal4py/sklearn.rst @@ -29,7 +29,7 @@ Deprecation Notice ------------------------------- Scikit-learn patching functionality in daal4py was deprecated and moved to a separate -package, `Intel(R) Extension for Scikit-learn* `_. +package, `Intel(R) Extension for Scikit-learn* `_. All future patches will be available only in Intel(R) Extension for Scikit-learn*. Please use the scikit-learn-intelex package instead of daal4py for the scikit-learn acceleration. diff --git a/doc/daal4py/streaming.rst b/doc/daal4py/streaming.rst index f29562453d..6c8e97dc2e 100644 --- a/doc/daal4py/streaming.rst +++ b/doc/daal4py/streaming.rst @@ -48,7 +48,7 @@ daal4py's streaming mode is as easy as follows: The streaming algorithms also accept arrays and DataFrames as input, e.g. the data can come from a stream rather than from multiple files. Here is an example which simulates a data stream using a generator which reads a file in chunks: -`SVD reading stream of data `_ +`SVD reading stream of data `_ Supported Algorithms and Examples --------------------------------- @@ -56,28 +56,28 @@ The following algorithms support streaming: - SVD (svd) - - `SVD `_ + - `SVD `_ - Linear Regression Training (linear_regression_training) - - `Linear Regression `_ + - `Linear Regression `_ - Ridge Regression Training (ridge_regression_training) - - `Ridge Regression `_ + - `Ridge Regression `_ - Multinomial Naive Bayes Training (multinomial_naive_bayes_training) - - `Naive Bayes `_ + - `Naive Bayes `_ - Moments of Low Order - - `Low Order Moments `_ + - `Low Order Moments `_ - Covariance - - `Covariance `_ + - `Covariance `_ - QR - - `QR `_ + - `QR `_ diff --git a/doc/sources/404.rst b/doc/sources/404.rst index 3060a3f9cc..9532f8db9b 100644 --- a/doc/sources/404.rst +++ b/doc/sources/404.rst @@ -24,5 +24,5 @@ Unfortunately, we could not find the page you were looking for. Try: - using :ref:`search ` to browse documentation - checking the table of contents on the left -- filing an `issue `_ or - starting a `discussion `_ on GitHub \ No newline at end of file +- filing an `issue `_ or + starting a `discussion `_ on GitHub \ No newline at end of file diff --git a/doc/sources/_templates/layout.html b/doc/sources/_templates/layout.html index 3f710964db..6d89aca80e 100644 --- a/doc/sources/_templates/layout.html +++ b/doc/sources/_templates/layout.html @@ -6,7 +6,7 @@ var wapLocalCode = 'us-en'; // Dynamically set per localized site, see mapping table for values var wapSection = "scikit-learn"; // WAP team will give you a unique section for your site // Load TMS - if(document.location.href.includes("intel.github.io/scikit-learn-intelex")){ + if(document.location.href.includes("uxlfoundation.github.io/scikit-learn-intelex")){ (function () { var url = 'https://www.intel.com/content/dam/www/global/wap/tms-loader.js'; // WAP file URL var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = url; diff --git a/doc/sources/algorithms.rst b/doc/sources/algorithms.rst index 4d165c1910..473255c0c2 100755 --- a/doc/sources/algorithms.rst +++ b/doc/sources/algorithms.rst @@ -540,4 +540,4 @@ Scikit-learn Tests Monkey-patched scikit-learn classes and functions passes scikit-learn's own test suite, with few exceptions, specified in `deselected_tests.yaml -`__. +`__. diff --git a/doc/sources/contribute.rst b/doc/sources/contribute.rst index 28283bd9d8..ff4cb901e9 100644 --- a/doc/sources/contribute.rst +++ b/doc/sources/contribute.rst @@ -23,7 +23,7 @@ This document explains how to participate in project conversations, log bugs and Licensing ---------------------------------- -Intel(R) Extension for Scikit-learn uses the `Apache 2.0 License `_. By contributing to the project, you agree to the license and copyright terms and release your own contributions under these terms. +Intel(R) Extension for Scikit-learn uses the `Apache 2.0 License `_. By contributing to the project, you agree to the license and copyright terms and release your own contributions under these terms. Pull Requests ---------------------------------- @@ -50,7 +50,7 @@ Code Style ------------------- We use `black `_ and `isort `_ formatters for Python* code. -The line length is 90 characters; use default options otherwise. You can find the linter configuration in `.pyproject.toml `_. +The line length is 90 characters; use default options otherwise. You can find the linter configuration in `.pyproject.toml `_. A GitHub* Action verifies if your changes comply with the output of the auto-formatting tools. diff --git a/doc/sources/distributed-mode.rst b/doc/sources/distributed-mode.rst index cfeee2c611..fa652a4c2b 100644 --- a/doc/sources/distributed-mode.rst +++ b/doc/sources/distributed-mode.rst @@ -20,12 +20,12 @@ Distributed Mode ================ |intelex| offers Single Program, Multiple Data (SPMD) supported interfaces for distributed computing. -Several `GPU-supported algorithms `_ +Several `GPU-supported algorithms `_ also provide distributed, multi-GPU computing capabilities via integration with ``mpi4py``. The prerequisites match those of GPU computing, along with an MPI backend of your choice (`Intel MPI recommended `_, available via ``impi-devel`` python package) and the ``mpi4py`` python package. If using |intelex| -`installed from sources `_, +`installed from sources `_, ensure that the spmd_backend is built. Note that |intelex| now supports GPU offloading to speed up MPI operations. This is supported automatically with @@ -39,14 +39,14 @@ data on device without this may lead to a runtime error): Estimators can be imported from the ``sklearnex.spmd`` module. Data should be distributed across multiple nodes as desired, and should be transfered to a dpctl or dpnp array before being passed to the estimator. View a full example of this process in the |intelex| repository, where many examples of our SPMD-supported estimators are -available: https://github.com/intel/scikit-learn-intelex/blob/main/examples/sklearnex/. To run: +available: https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/sklearnex/. To run: :: mpirun -n 4 python linear_regression_spmd.py Note that additional mpirun arguments can be added as desired. SPMD-supported estimators are listed in the -`algorithms support documentation `_. +`algorithms support documentation `_. Additionally, daal4py offers some distributed functionality, see `documentation `_ for further details. diff --git a/doc/sources/index.rst b/doc/sources/index.rst index 4663cd1d5b..cc7becdb8e 100755 --- a/doc/sources/index.rst +++ b/doc/sources/index.rst @@ -15,7 +15,7 @@ .. *******************************************************************************/ .. |intelex_repo| replace:: |intelex| repository -.. _intelex_repo: https://github.com/intel/scikit-learn-intelex +.. _intelex_repo: https://github.com/uxlfoundation/scikit-learn-intelex .. _index: diff --git a/doc/sources/license.rst b/doc/sources/license.rst index df68abaea6..2fa5b9dba8 100644 --- a/doc/sources/license.rst +++ b/doc/sources/license.rst @@ -20,4 +20,4 @@ License ############################################ -License: https://github.com/intel/scikit-learn-intelex/blob/main/LICENSE \ No newline at end of file +License: https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/LICENSE \ No newline at end of file diff --git a/doc/sources/quick-start.rst b/doc/sources/quick-start.rst index bc6ac8798a..deef962868 100644 --- a/doc/sources/quick-start.rst +++ b/doc/sources/quick-start.rst @@ -15,7 +15,7 @@ .. *******************************************************************************/ .. |intelex_repo| replace:: |intelex| repository -.. _intelex_repo: https://github.com/intel/scikit-learn-intelex +.. _intelex_repo: https://github.com/uxlfoundation/scikit-learn-intelex #################### Quick Start @@ -311,7 +311,7 @@ To prevent version conflicts, we recommend installing `scikit-learn-intelex` int Build from Sources ********************** -See `Installation instructions `_ to build |intelex| from the sources. +See `Installation instructions `_ to build |intelex| from the sources. Install Intel*(R) AI Tools **************************** @@ -321,7 +321,7 @@ Download the Intel AI Tools `here `_ for each version of IntelĀ® Extension for Scikit-learn*. +See the `Release Notes `_ for each version of IntelĀ® Extension for Scikit-learn*. System Requirements -------------------- diff --git a/doc/sources/samples.rst b/doc/sources/samples.rst index 4ca25f6d92..00071f0fad 100644 --- a/doc/sources/samples.rst +++ b/doc/sources/samples.rst @@ -22,7 +22,7 @@ Samples The following samples are also provided as Jupyter notebooks in |intelex| repository. If you want to run them locally, refer to `these instructions -`_. +`_. .. rubric:: Classification Tasks diff --git a/doc/sources/support.rst b/doc/sources/support.rst index 03a2dddadb..9548ec2ab7 100644 --- a/doc/sources/support.rst +++ b/doc/sources/support.rst @@ -27,7 +27,7 @@ Use the following methods if you face any challenges. Issues ---------------------------------- -If you have a problem, check out the `GitHub Issues `_ to see if the issue you want to address is already reported. +If you have a problem, check out the `GitHub Issues `_ to see if the issue you want to address is already reported. You may find users that have encountered the same bug or have similar ideas for changes or updates. diff --git a/examples/notebooks/ElasticNet.ipynb b/examples/notebooks/ElasticNet.ipynb index 29e5dca851..0dca82f35a 100644 --- a/examples/notebooks/ElasticNet.ipynb +++ b/examples/notebooks/ElasticNet.ipynb @@ -149,7 +149,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -164,7 +164,7 @@ "id": "20c5ab48", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/README.md b/examples/notebooks/README.md index 26320057e8..b19a2a3b08 100644 --- a/examples/notebooks/README.md +++ b/examples/notebooks/README.md @@ -21,14 +21,14 @@ jupyter notebook --notebook-dir=./ --ip=* --no-browser | Algorithm | Workload | Task | Notebook | Scikit-learn estimator| | :----------------------:| :------------: | :---------------:| :------------: | :-------------------:| -| LogisticRegression | CIFAR-100 | Š”lassification | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/logistictic_regression_cifar.ipynb) | [sklearn.linear_model.LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) | -| SVC | Adult | Š”lassification | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/svc_adult.ipynb) | [sklearn.svm.SVC](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) | -| KNeighborsClassifier | MNIST | Š”lassification | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/knn_mnist.ipynb) | [sklearn.neighbors.KNeighborsClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html) | -| NuSVR | Medical charges | Regression | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/nusvr_medical_charges.ipynb) | [sklearn.svm.NuSVR](https://scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html) | -| RandomForestRegressor | Yolanda | Regression | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/random_forest_yolanda.ipynb) | [sklearn.ensemble.RandomForestRegressor](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html) | -| Ridge | Airlines DepDelay | Regression | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/ridge_regression.ipynb) | [sklearn.linear_model.Ridge](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html) | -| ElasticNet | Airlines DepDelay | Regression | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/ElasticNet.ipynb) | [sklearn.linear_model.ElasticNet](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html) | -| Lasso | YearPredictionMSD | Regression | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/lasso_regression.ipynb) | [sklearn.linear_model.Lasso](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html) | -| Linear Regression | YearPredictionMSD | Regression | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/linear_regression.ipynb) | [sklearn.linear_model.LinearRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html) | -| KMeans | Spoken arabic digit | Clustering | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/kmeans.ipynb) | [sklearn.cluster.KMeans](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html) | -| DBSCAN | Spoken arabic digit | Clustering | [View source on GitHub](https://github.com/intel/scikit-learn-intelex/blob/main/examples/notebooks/dbscan.ipynb) | [sklearn.cluster.DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) | +| LogisticRegression | CIFAR-100 | Š”lassification | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/logistictic_regression_cifar.ipynb) | [sklearn.linear_model.LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) | +| SVC | Adult | Š”lassification | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/svc_adult.ipynb) | [sklearn.svm.SVC](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) | +| KNeighborsClassifier | MNIST | Š”lassification | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/knn_mnist.ipynb) | [sklearn.neighbors.KNeighborsClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html) | +| NuSVR | Medical charges | Regression | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/nusvr_medical_charges.ipynb) | [sklearn.svm.NuSVR](https://scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html) | +| RandomForestRegressor | Yolanda | Regression | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/random_forest_yolanda.ipynb) | [sklearn.ensemble.RandomForestRegressor](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html) | +| Ridge | Airlines DepDelay | Regression | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/ridge_regression.ipynb) | [sklearn.linear_model.Ridge](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html) | +| ElasticNet | Airlines DepDelay | Regression | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/ElasticNet.ipynb) | [sklearn.linear_model.ElasticNet](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html) | +| Lasso | YearPredictionMSD | Regression | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/lasso_regression.ipynb) | [sklearn.linear_model.Lasso](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html) | +| Linear Regression | YearPredictionMSD | Regression | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/linear_regression.ipynb) | [sklearn.linear_model.LinearRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html) | +| KMeans | Spoken arabic digit | Clustering | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/kmeans.ipynb) | [sklearn.cluster.KMeans](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html) | +| DBSCAN | Spoken arabic digit | Clustering | [View source on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/dbscan.ipynb) | [sklearn.cluster.DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) | diff --git a/examples/notebooks/dbscan.ipynb b/examples/notebooks/dbscan.ipynb index d6e5c92653..f7d1c5f523 100644 --- a/examples/notebooks/dbscan.ipynb +++ b/examples/notebooks/dbscan.ipynb @@ -113,7 +113,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -128,7 +128,7 @@ "id": "20c5ab48", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/kmeans.ipynb b/examples/notebooks/kmeans.ipynb index df09f8ded5..8723260525 100644 --- a/examples/notebooks/kmeans.ipynb +++ b/examples/notebooks/kmeans.ipynb @@ -124,7 +124,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -139,7 +139,7 @@ "id": "20c5ab48", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/knn_mnist.ipynb b/examples/notebooks/knn_mnist.ipynb index b8604d70f0..9a757d8c15 100644 --- a/examples/notebooks/knn_mnist.ipynb +++ b/examples/notebooks/knn_mnist.ipynb @@ -89,7 +89,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -104,7 +104,7 @@ "id": "6bb14ac8", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/lasso_regression.ipynb b/examples/notebooks/lasso_regression.ipynb index 967d0d4e54..40fbe00f8e 100644 --- a/examples/notebooks/lasso_regression.ipynb +++ b/examples/notebooks/lasso_regression.ipynb @@ -147,7 +147,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -162,7 +162,7 @@ "id": "20c5ab48", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/linear_regression.ipynb b/examples/notebooks/linear_regression.ipynb index 508ee06d8c..22ad54ce8b 100644 --- a/examples/notebooks/linear_regression.ipynb +++ b/examples/notebooks/linear_regression.ipynb @@ -147,7 +147,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -162,7 +162,7 @@ "id": "20c5ab48", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/logistictic_regression_cifar.ipynb b/examples/notebooks/logistictic_regression_cifar.ipynb index 43727804d7..1b80bb8d51 100644 --- a/examples/notebooks/logistictic_regression_cifar.ipynb +++ b/examples/notebooks/logistictic_regression_cifar.ipynb @@ -93,7 +93,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -108,7 +108,7 @@ "id": "6bb14ac8", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/nusvr_medical_charges.ipynb b/examples/notebooks/nusvr_medical_charges.ipynb index 8c72c1b71d..8e644fcce5 100644 --- a/examples/notebooks/nusvr_medical_charges.ipynb +++ b/examples/notebooks/nusvr_medical_charges.ipynb @@ -118,7 +118,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -133,7 +133,7 @@ "id": "6bb14ac8", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/random_forest_yolanda.ipynb b/examples/notebooks/random_forest_yolanda.ipynb index 276284ed9b..26e58fdaa8 100644 --- a/examples/notebooks/random_forest_yolanda.ipynb +++ b/examples/notebooks/random_forest_yolanda.ipynb @@ -89,7 +89,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -104,7 +104,7 @@ "id": "6bb14ac8", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/ridge_regression.ipynb b/examples/notebooks/ridge_regression.ipynb index 1c159a13ae..0f53fc1b66 100644 --- a/examples/notebooks/ridge_regression.ipynb +++ b/examples/notebooks/ridge_regression.ipynb @@ -154,7 +154,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -169,7 +169,7 @@ "id": "20c5ab48", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/latest/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/svc_adult.ipynb b/examples/notebooks/svc_adult.ipynb index 9e49bcfecd..ecd27fb784 100644 --- a/examples/notebooks/svc_adult.ipynb +++ b/examples/notebooks/svc_adult.ipynb @@ -77,7 +77,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -92,7 +92,7 @@ "id": "6bb14ac8", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/examples/notebooks/tsne.ipynb b/examples/notebooks/tsne.ipynb index 99ad8fcefd..14242f4ad8 100644 --- a/examples/notebooks/tsne.ipynb +++ b/examples/notebooks/tsne.ipynb @@ -71,7 +71,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Intel(R) Extension for Scikit-learn* enabled (https://github.com/intel/scikit-learn-intelex)\n" + "Intel(R) Extension for Scikit-learn* enabled (https://github.com/uxlfoundation/scikit-learn-intelex)\n" ] } ], @@ -86,7 +86,7 @@ "id": "6bb14ac8", "metadata": {}, "source": [ - "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://intel.github.io/scikit-learn-intelex/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/intel/scikit-learn-intelex/issues)." + "IntelĀ® Extension for Scikit-learn patching affects performance of specific Scikit-learn functionality. Refer to the [list of supported algorithms and parameters](https://uxlfoundation.github.io/scikit-learn-intelex/algorithms.html) for details. In cases when unsupported parameters are used, the package fallbacks into original Scikit-learn. If the patching does not cover your scenarios, [submit an issue on GitHub](https://github.com/uxlfoundation/scikit-learn-intelex/issues)." ] }, { diff --git a/scripts/CMakeLists.txt b/scripts/CMakeLists.txt index 4b2eb5480b..ed6a781b76 100644 --- a/scripts/CMakeLists.txt +++ b/scripts/CMakeLists.txt @@ -18,7 +18,7 @@ cmake_minimum_required(VERSION 3.13 FATAL_ERROR) project("oneDAL python interface" LANGUAGES CXX - HOMEPAGE_URL https://github.com/oneapi-src/oneDAL + HOMEPAGE_URL https://github.com/uxlfoundation/oneDAL ) set(CMAKE_BUILD_TYPE Release) diff --git a/setup.py b/setup.py index 5059991b27..8166f00d07 100644 --- a/setup.py +++ b/setup.py @@ -483,9 +483,9 @@ def run(self): project_urls = { - "Bug Tracker": "https://github.com/intel/scikit-learn-intelex", + "Bug Tracker": "https://github.com/uxlfoundation/scikit-learn-intelex", "Documentation": "https://intelpython.github.io/daal4py/", - "Source Code": "https://github.com/intel/scikit-learn-intelex/daal4py", + "Source Code": "https://github.com/uxlfoundation/scikit-learn-intelex/daal4py", } with open("README.md", "r", encoding="utf8") as f: @@ -573,7 +573,7 @@ def run(self): license="Apache-2.0", author="Intel Corporation", version=sklearnex_version, - url="https://github.com/intel/scikit-learn-intelex", + url="https://github.com/uxlfoundation/scikit-learn-intelex", author_email="onedal.maintainers@intel.com", maintainer_email="onedal.maintainers@intel.com", project_urls=project_urls, diff --git a/sklearnex/_utils.py b/sklearnex/_utils.py index 651ac72654..6a1b0ac06c 100755 --- a/sklearnex/_utils.py +++ b/sklearnex/_utils.py @@ -140,4 +140,4 @@ def _doc_link_module(self) -> str: def _doc_link_template(self) -> str: module_path, _ = self.__class__.__module__.rsplit(".", 1) class_name = self.__class__.__name__ - return f"https://intel.github.io/scikit-learn-intelex/latest/non-scikit-algorithms.html#{module_path}.{class_name}" + return f"https://uxlfoundation.github.io/scikit-learn-intelex/latest/non-scikit-algorithms.html#{module_path}.{class_name}" diff --git a/sklearnex/dispatcher.py b/sklearnex/dispatcher.py index c15459cd6e..b5099b5d1e 100644 --- a/sklearnex/dispatcher.py +++ b/sklearnex/dispatcher.py @@ -483,7 +483,7 @@ def patch_sklearn(name=None, verbose=True, global_patch=False, preview=False): if verbose and sys.stderr is not None: sys.stderr.write( "Intel(R) Extension for Scikit-learn* enabled " - "(https://github.com/intel/scikit-learn-intelex)\n" + "(https://github.com/uxlfoundation/scikit-learn-intelex)\n" )