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Releases: uxlfoundation/scikit-learn-intelex

Intel® Extension for Scikit-learn* 2024.1.0

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@maria-Petrova maria-Petrova released this 24 Jan 21:51
bc84012

Intel® Extension for Scikit-learn* is happy to introduce 2024.1.0 release!

🚨 What's New

  • New Intel® Extension for Scikit-learn* functionality:
    • SHAP support for symmetric CatBoost models
    • Added oneDAL LinReg and Covariance hyperparameters API
    • Added LogisticRegression interface to the preview section
    • Initial support of n_jobs parameter

Acknowledgements

Thanks to everyone who helped us make 2024.1.0 release possible!

@Alexsandruss, @icfaust, @napetrov, @ahuber21, @ethanglaser, @samir-nasibli, @aepanchi, @olegkkruglov, @razdoburdin, @KulikovNikita, @maria-Petrova, @avolkov-intel

Full Changelog: 2024.0.1...2024.1.0

Intel® Extension for Scikit-learn* 2024.0.1

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@maria-Petrova maria-Petrova released this 30 Nov 17:53
7a32a0a

Intel® Extension for Scikit-learn* is happy to introduce 2024.0.1 release!

🚨 What's New

  • New Intel(R) Extension for Scikit-learn* functionality:
    • Linear Regression and ensemble algorithms are moved out of preview namespace
  • New Model Builders functionality:
    • SHAP calculation is added to GBT regression

🔨 Library Engineering

  • Added Python 3.12 support for daal4py and Intel(R) Extension for Scikit-learn* packages

📚 Support Materials

Faster XGBoost*, LightGBM, and CatBoost Inference on the CPU
PS-S3-Ep23-with-scikit-learn-intelex
pss3e23 fusion_model with scikit-learn-intelex
PS S3E25: Faster regression tuning with sklearnex

🔀 Adoption

TPOT2 AutoML integration

Acknowledgements

Thanks to everyone who helped us make 2024.0.1 release possible!

@Alexsandruss, @icfaust, @napetrov, @ahuber21, @ethanglaser, @samir-nasibli, @aepanchi, @olegkkruglov, @razdoburdin, @KulikovNikita, @maria-Petrova, @avolkov-intel

Intel(R) Extension for Scikit-learn* 2024.0.0

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@maria-Petrova maria-Petrova released this 21 Nov 14:27
e7b669f

Intel(R) Extension for Scikit-learn* is happy to introduce 2024.0 release!

What's New

  • New functionality:
    • DBSCAN and SPMD DBSCAN algorithms

Acknowledgements

Thanks to everyone who helped us make 2024.0 release possible!

@Alexsandruss, @icfaust, @napetrov, @ahuber21, @ethanglaser, @samir-nasibli, @aepanchi, @olegkkruglov, @razdoburdin, @KulikovNikita, @maria-Petrova, @avolkov-intel

Intel® Extension for Scikit-learn 2023.2.1

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@maria-Petrova maria-Petrova released this 24 Jul 18:30
12b963a

The release of Intel® Extension for Scikit-learn 2023.2.1 introduces the following changes:

🚨 What's New

Intel® Extension for Scikit-learn 2023.2.0

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@maria-Petrova maria-Petrova released this 24 Jul 16:24
9d1c4e9

The release of Intel® Extension for Scikit-learn 2023.2.0 introduces the following changes:

❌ Deprecation Notice

  • The compression functionality in the Intel® oneDAL library is deprecated. Starting with the 2024.0 release, oneDAL will not support the compression functionality
  • The DAAL CPP SYCL Interfaces in the Intel® oneDAL library are deprecated. Starting with the 2024.0 release, oneDAL will not support the DAAL CPP SYCL Interfaces
  • The Java* interfaces in the Intel® oneDAL library are marked as deprecated. The future releases of the oneDAL library may no longer include support for these Java* interfaces
  • ABI compatibility is to be broken as part of the 2024.0 release of Intel® oneDAL. The library’s major version is to be incremented to two to enforce the relinking of existing applications
  • macOS* support is deprecated for oneDAL. The 2023.x releases are the last to provide it

🛠️ Library Engineering

  • CSR tables interface has been changed and moved from detail namespace

🚨 What's New

  • Introduced new Intel® oneDAL functionality:
    • Distributed KMeans++ algorithm
    • Logistic Loss objective algorithm
  • Introduced new functionality for Intel® Extension for Scikit-learn:
    • NaN(missing values) support was added to Model Builders
  • Improved performance for the following Intel® Extension for Scikit-learn algorithms:
    • Model Builders performance has been improved up to 2x

Intel® Extension for Scikit-learn 2023.1.1

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@maria-Petrova maria-Petrova released this 04 May 11:41
4abff0d

The release of Intel® Extension for Scikit-learn 2023.1.1 introduces the following changes:

🚨 What's New

Intel® Extension for Scikit-learn 2023.1.0

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@maria-Petrova maria-Petrova released this 04 May 11:33
94744b2

The release of Intel® Extension for Scikit-learn 2023.1 introduces the following changes:

📚Support Materials

🛠️ Library Engineering

  • Reduced the size of Intel® oneDAL library by approximately ~30%

🚨 What's New

  • Introduced new functionality for Intel® Extension for Scikit-learn:
    • Enabled PCA, Linear Regression, Random Forest algorithms and SPMD policy as preview
    • Scikit-learn 1.2 support
    • sklearn_is_patched() function added to validate status of algorithms patching
  • Improved performance for the following Intel® Extension for Scikit-learn algorithms:
    • t-SNE for “Burnes-Hut” algorithm
    • SVM algorithm for single row inference

❗ Known Issues

  • In certain conditions DAAL SYCL interface might hang with L0 backend – please use oneDAL DPC interfaces instead. If older interfaces are required OpenCL backend can be used as workaround.

Intel® Extension for Scikit-learn 2023.0.1

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@maria-Petrova maria-Petrova released this 04 May 11:28
6c27da3

The release of Intel® Extension for Scikit-learn 2023.0.1 introduces the following changes:

🚨 What's New

  • Performance improvements for tSNE algorithm 5275eba
  • Fixes for balanced classes and number of iterations in SVM 14849ee, 4872a8e, 9d0a05b
  • Fix for gamma parameter in KMeans 1dca20c

Intel® Extension for Scikit-learn 2023.0.0

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@maria-Petrova maria-Petrova released this 02 May 17:19

The release of Intel® Extension for Scikit-learn 2023.0 introduces the following changes:

🚨 What's New

  • Introduced new Intel® oneDAL functionality:
    • DPC++ interface for Linear Regression algorithm

❗ Known Issues

  • Intel® Extension for Scikit-learn SVC.fit and KNN.fit do not support GPU
  • Most Intel® Extension for Scikit-learn sycl examples fail when using GPU context
  • Running the Random Forest algorithm with versions 2021.7.1 and 2023.0 of scikit-learn-intelex on the 2nd Generation Intel® Xeon® Scalable Processors, formerly Cascade Lake may result in an 'Illegal instruction' error.
    • No workaround is currently available for this issue.
    • Recommendation: Use an older version of scikit-learn-intelex until the issue is fixed in a future release.

Intel(R) Extension for Scikit-learn 2021.7.1

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@Alexsandruss Alexsandruss released this 01 Dec 14:40
9764b19

The release Intel® Extension for Scikit-learn 2021.7.1 introduces the following changes:

📚 Support Materials

🚨 What's New

  • oneAPI interface for kNN regression
  • Fix for wrong column names of pandas DataFrame in sklearn.model_selection.train_test_split patched function