Intel(R) Extension for Scikit-learn 2021.6

[Alexsandruss]

The release Intel® Extension for Scikit-learn 2021.6 introduces the following changes:

📚 Support Materials

Kaggle kernels:

• Fast Feature Importance using scikit-learn-intelex
• [Tabular Playground Series - December 2021] Fast Feature Importance with sklearnex
• [Tabular Playground Series - December 2021] SVC with sklearnex 20x speedup
• [Tabular Playground Series - January 2022] Fast PyCaret with Scikit-learn-Intelex
• [Tabular Playground Series - February 2022] KNN with sklearnex 13x speedup
• Fast SVM for Sparse Data from NLP Problem
• Introduction to scikit-learn-intelex
• [Datasets] Fast Feature Importance using sklearnex
• [Tabular Playground Series - March 2022] Fast workflow using scikit-learn-intelex

🛠️ Library Engineering

• Reduced the size of oneDAL python run-time package by approximately 8%
• Added Python 3.10 support for daal4py and Intel(R) Extension for Scikit-learn packages

🚨 What's new

• Improved performance for the following Intel® Extension for Scikit-learn algorithms:

  • t-SNE for “Burnes-Hut” algorithm

• Introduced new functionality for Intel® Extension for Scikit-learn:

  • Manhattan, Minkowski, Chebyshev and Cosine distances for KNeighborsClassifier and NearestNeighbors with “brute” algorithm

• Fixed the following issues in Intel® Extension for Scikit-learn:

  • An issue with the search of common data type in pandas DataFrame
  • Patching overhead of finiteness checker for specific small data sizes
  • Incorrect values in a tree visualization with plot_tree function in RandomForestClassifier
  • Unexpected error for device strings in {device}:{device_index} format while using config context

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This discussion was created from the release Intel(R) Extension for Scikit-learn 2021.6.