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README.md

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# Machine Learning Benchmarks <!-- omit in toc -->
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[![Build Status](https://dev.azure.com/daal/scikit-learn_bench/_apis/build/status/IntelPython.scikit-learn_bench?branchName=master)](https://dev.azure.com/daal/scikit-learn_bench/_build/latest?definitionId=8&branchName=master)
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[![Build Status](https://dev.azure.com/daal/scikit-learn_bench/_apis/build/status/IntelPython.scikit-learn_bench?branchName=main)](https://dev.azure.com/daal/scikit-learn_bench/_build/latest?definitionId=8&branchName=main)
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**Machine Learning Benchmarks** contains implementations of machine learning algorithms
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across data analytics frameworks. Scikit-learn_bench can be extended to add new frameworks
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Options:
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- ``--configs``: specify the path to a configuration file or a folder that contains configuration files.
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- ``--no-intel-optimized``: use Scikit-learn without [Intel(R) Extension for Scikit-learn*](#intelr-extension-for-scikit-learn-support). Now available for [scikit-learn benchmarks](https://github.com/IntelPython/scikit-learn_bench/tree/master/sklearn_bench). By default, the runner uses Intel(R) Extension for Scikit-learn.
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- ``--no-intel-optimized``: use Scikit-learn without [Intel(R) Extension for Scikit-learn*](#intelr-extension-for-scikit-learn-support). Now available for [scikit-learn benchmarks](https://github.com/IntelPython/scikit-learn_bench/tree/main/sklearn_bench). By default, the runner uses Intel(R) Extension for Scikit-learn.
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- ``--output-file``: specify the name of the output file for the benchmark result. The default name is `result.json`
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- ``--report``: create an Excel report based on benchmark results. The `openpyxl` library is required.
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- ``--dummy-run``: run configuration parser and dataset generation without benchmarks running.
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The configuration of benchmarks allows you to select the frameworks to run, select datasets for measurements and configure the parameters of the algorithms.
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You can configure benchmarks by editing a config file. Check [config.json schema](https://github.com/IntelPython/scikit-learn_bench/blob/master/configs/README.md) for more details.
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You can configure benchmarks by editing a config file. Check [config.json schema](https://github.com/IntelPython/scikit-learn_bench/blob/main/configs/README.md) for more details.
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## Benchmark supported algorithms
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When you run scikit-learn benchmarks on CPU, [Intel(R) Extension for Scikit-learn](https://github.com/intel/scikit-learn-intelex) is used by default. Use the ``--no-intel-optimized`` option to run the benchmarks without the extension.
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For the algorithms with both CPU and GPU support, you may use the same [configuration file](https://github.com/IntelPython/scikit-learn_bench/blob/master/configs/skl_xpu_config.json) to run the scikit-learn benchmarks on CPU and GPU.
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For the algorithms with both CPU and GPU support, you may use the same [configuration file](https://github.com/IntelPython/scikit-learn_bench/blob/main/configs/skl_xpu_config.json) to run the scikit-learn benchmarks on CPU and GPU.
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## Algorithm parameters
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